Optimization of Phloretin-loaded Nanospanlastics for Targeting of FAS/SREBP1c/AMPK/ OB-Rb Signaling Pathway in HFD-induced Obesity

OBJECTIVES

Obese patients are at increased risk for CVD, which is the main cause of premature death and has been a major cause of disability and ill health in recent years. PTN, a natural dihydrochalcone flavonoid, has a variety of pharmacological characteristics. This article aimed to prepare PTN-NSLs to evaluate their anti-obesity activity.

METHODS

Morphology, Particle size, zeta potential, UV-vis, entrapment efficiency, FT-IR spectra, and an in vitro release study of PTN-NSLs were described. PTN-NSLs were also tested for their anti-obesity properties in obese rats. The LD50 of PTN-NSLs was calculated, as was the 1/20 LD50 prepared for the treatment of obese rats. Also, the level of glycemic, oxidative stress and inflammatory biomarkers were estimated in the obese rat's model.

RESULTS

The synthesized PTN-NSLs were uniform, spherically shaped, and well dispersed with no aggregation noted, with a size range of 114.06 ± 8.35 nm. The measured zeta potential value of PTN-NSLs was -32.50.8 mv. Also, the UV spectra of PTN and PTN-NSLs have strong absorption at 225 and 285 nm. Also, the LD50 of PTN-NSLs was found to be 2750 mg/kg.b.w. Moreover, administrating obese rats with PTN-NSLs resulted in improved glycemic features as well as GSH, SOD, GPx, GR, IL10, TBARs, and IL-6 levels, as well as attenuated FAS, SREBP1c, AMPK, ACO, CPT1, and OB-Rb gene expression.

CONCLUSIONS

Administration of PTN-NSLs significantly attenuated the levels of glycemic, oxidative stress, and inflammatory biomarkers. The biochemical and PCR findings are aided by histological investigations. Also, the present findings imply that PTN-NSLs might be a promising pharmacological tool for the treatment of obesity-related diseases.

Ethylene induced AcNAC3 and AcNAC4 take part in ethylene synthesis through mediating AcACO1 during kiwifruit (Actinidia chinensis) ripening

BACKGROUND

Ethylene plays a vital role in the ripening process of kiwifruit. A terrific amount of transcription factors (TFs) have been shown to regulate ethylene synthesis in various fruits.

RESULTS

In this research, two new NAC TFs, named AcNAC3 and AcNAC4, were isolated from kiwifruit, which belonged to NAM subfamily. Bioinformatics analysis showed that both AcNAC3 and AcNAC4 were hydrophilic proteins with similar three-dimensional structures. The expression levels of AcNAC3, AcNAC4 and AcACO1 increased during kiwifruit ripening, as well as were induced by ethylene and repressed by 1-methylcyclopropene (1-MCP). Correlation analysis exhibited that ethylene production was positively correlated with the expression levels of AcNAC3, AcNAC4 and AcACO1. Moreover, both AcNAC3 and AcNAC4 acted as transcriptional activators and could bind to and activate AcACO1 promoter.

CONCLUSION

All results unveiled that the ethylene-induced AcNAC3 and AcNAC4 were transcriptional activators, and might participate in kiwifruit ripening and ethylene biosynthesis through activating AcACO1, providing a new insight of ethylene synthetic regulation during kiwifruit ripening. © 2024 Society of Chemical Industry.

PPARγ attenuates cellular senescence of alveolar macrophages in asthma-COPD overlap

BACKGROUND

Asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) represents a complex condition characterized by shared clinical and pathophysiological features of asthma and COPD in older individuals. However, the pathophysiology of ACO remains unexplored. We aimed to identify the major inflammatory cells in ACO, examine senescence within these cells, and elucidate the genes responsible for regulating senescence.

METHODS

Bioinformatic analyses were performed to investigate major cell types and cellular senescence signatures in a public single-cell RNA sequencing (scRNA-Seq) dataset derived from the lung tissues of patients with ACO. Similar analyses were carried out in an independent cohort study Immune Mechanisms Severe Asthma (IMSA), which included bulk RNA-Seq and CyTOF data from bronchoalveolar lavage fluid (BALF) samples.

RESULTS

The analysis of the scRNA-Seq data revealed that monocytes/ macrophages were the predominant cell type in the lung tissues of ACO patients, constituting more than 50% of the cells analyzed. Lung monocytes/macrophages from patients with ACO exhibited a lower prevalence of senescence as defined by lower enrichment scores of SenMayo and expression levels of cellular senescence markers. Intriguingly, analysis of the IMSA dataset showed similar results in patients with severe asthma. They also exhibited a lower prevalence of senescence, particularly in airway CD206 + macrophages, along with increased cytokine expression (e.g., IL-4, IL-13, and IL-22). Further exploration identified alveolar macrophages as a major subtype of monocytes/macrophages driving cellular senescence in ACO. Differentially expressed genes related to oxidation-reduction, cytokines, and growth factors were implicated in regulating senescence in alveolar macrophages. PPARγ (Peroxisome Proliferator-Activated Receptor Gamma) emerged as one of the predominant regulators modulating the senescent signature of alveolar macrophages in ACO.

CONCLUSION

The findings suggest that senescence in macrophages, particularly alveolar macrophages, plays a crucial role in the pathophysiology of ACO. Furthermore, PPARγ may represent a potential therapeutic target for interventions aimed at modulating senescence-associated processes in ACO.Key words ACO, Asthma, COPD, Macrophages, Senescence, PPARγ.

Optimizing Driving Parameters of the Jumbo Drill Efficiently with XGBoost-DRWIACO Framework: Applied to Increase the Feed Speed

The jumbo drill is a commonly used driving equipment in tunnel engineering. One of the key decision-making issues for reducing tunnel construction costs is to optimize the main driving parameters to increase the feed speed of the jumbo drill. The optimization of the driving parameters is supposed to meet the requirements of high reliability and efficiency due to the high risk and complex working conditions in tunnel engineering. The flaws of the existing optimization algorithms for driving parameter optimization lie in the low accuracy of the evaluation functions under complex working conditions and the low efficiency of the algorithms. To address the above problems, a driving parameter optimization method based on the XGBoost-DRWIACO framework with high accuracy and efficiency is proposed. A data-driven prediction model for feed speed based on XGBoost is established as the evaluation function, which has high accuracy under complex working conditions and ensures the high reliability of the optimized results. Meanwhile, an improved ant colony algorithm based on dimension reduction while iterating strategy (DRWIACO) is proposed. DRWIACO is supposed to improve efficiency by resolving inefficient iterations of the ant colony algorithm (ACO), which is manifested as falling into local optimum, converging slowly and converging with a slight fluctuation in a certain dimension. Experimental results show that the error by the proposed framework is less than 10%, and the efficiency is increased by over 30% compared with the comparison methods, which meets the requirements of high reliability and efficiency for tunnel construction. More importantly, the construction cost is reduced by 19% compared with the actual feed speed, which improves the economic benefits.

Early-life house dust mite aeroallergen exposure augments cigarette smoke-induced myeloid inflammation and emphysema in mice

BACKGROUND

Longitudinal studies have identified childhood asthma as a risk factor for obstructive pulmonary disease (COPD) and asthma-COPD overlap (ACO) where persistent airflow limitation can develop more aggressively. However, a causal link between childhood asthma and COPD/ACO remains to be established. Our study aimed to model the natural history of childhood asthma and COPD and to investigate the cellular/molecular mechanisms that drive disease progression.

METHODS

Allergic airways disease was established in three-week-old young C57BL/6 mice using house dust mite (HDM) extract. Mice were subsequently exposed to cigarette smoke (CS) and HDM for 8 weeks. Airspace enlargement (emphysema) was measured by the mean linear intercept method. Flow cytometry was utilised to phenotype lung immune cells. Bulk RNA-sequencing was performed on lung tissue. Volatile organic compounds (VOCs) in bronchoalveolar lavage-fluid were analysed to screen for disease-specific biomarkers.

RESULTS

Chronic CS exposure induced emphysema that was significantly augmented by HDM challenge. Increased emphysematous changes were associated with more abundant immune cell lung infiltration consisting of neutrophils, interstitial macrophages, eosinophils and lymphocytes. Transcriptomic analyses identified a gene signature where disease-specific changes induced by HDM or CS alone were conserved in the HDM-CS group, and further revealed an enrichment of Mmp12, Il33 and Il13, and gene expression consistent with greater expansion of alternatively activated macrophages. VOC analysis also identified four compounds increased by CS exposure that were paradoxically reduced in the HDM-CS group.

CONCLUSIONS

Early-life allergic airways disease worsened emphysematous lung pathology in CS-exposed mice and markedly alters the lung transcriptome.

Functional mechanism study of the allelochemical myrigalone A identifies a group of ultrapotent inhibitors of ethylene biosynthesis in plants

Allelochemicals represent a class of natural products released by plants as root, leaf, and fruit exudates that interfere with the growth and survival of neighboring plants. Understanding how allelochemicals function to regulate plant responses may provide valuable new approaches to better control plant function. One such allelochemical, Myrigalone A (MyA) produced by Myrica gale, inhibits seed germination and seedling growth through an unknown mechanism. Here, we investigate MyA using the tractable model Dictyostelium discoideum and reveal that its activity depends on the conserved homolog of the plant ethylene synthesis protein 1-aminocyclopropane-1-carboxylic acid oxidase (ACO). Furthermore, in silico modeling predicts the direct binding of MyA to ACO within the catalytic pocket. In D. discoideum, ablation of ACO mimics the MyA-dependent developmental delay, which is partially restored by exogenous ethylene, and MyA reduces ethylene production. In Arabidopsis thaliana, MyA treatment delays seed germination, and this effect is rescued by exogenous ethylene. It also mimics the effect of established ACO inhibitors on root and hypocotyl extension, blocks ethylene-dependent root hair production, and reduces ethylene production. Finally, in silico binding analyses identify a range of highly potent ethylene inhibitors that block ethylene-dependent response and reduce ethylene production in Arabidopsis. Thus, we demonstrate a molecular mechanism by which the allelochemical MyA reduces ethylene biosynthesis and identify a range of ultrapotent inhibitors of ethylene-regulated responses.

PPARγ Attenuates Cellular Senescence of Alveolar Macrophages in Asthma- COPD Overlap

Asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) represents a complex condition characterized by shared clinical and pathophysiological features of asthma and COPD in older individuals. However, the pathophysiology of ACO remains unexplored. We aimed to identify the major inflammatory cells in ACO, examine senescence within these cells, and elucidate the genes responsible for regulating senescence. Bioinformatic analyses were performed to investigate major cell types and cellular senescence signatures in a public single-cell RNA sequencing (scRNA-Seq) dataset derived from the lung tissues of patients with ACO. Similar analyses were carried out in an independent cohort study Immune Mechanisms Severe Asthma (IMSA), which included bulk RNA-Seq and CyTOF data from bronchoalveolar lavage fluid (BALF) samples. The analysis of the scRNA-Seq data revealed that monocytes/ macrophages were the predominant cell type in the lung tissues of ACO patients, constituting more than 50% of the cells analyzed. Lung monocytes/macrophages from patients with ACO exhibited a lower prevalence of senescence as defined by lower enrichment scores of SenMayo and expression levels of cellular senescence markers. Intriguingly, analysis of the IMSA dataset showed similar results in patients with severe asthma. They also exhibited a lower prevalence of senescence, particularly in airway CD206 + macrophages, along with increased cytokine expression (e.g., IL-4, IL-13, and IL-22). Further exploration identified alveolar macrophages as a major subtype of monocytes/macrophages driving cellular senescence in ACO. Differentially expressed genes related to oxidation-reduction, cytokines, and growth factors were implicated in regulating senescence in alveolar macrophages. PPARγ (Peroxisome Proliferator-Activated Receptor Gamma) emerged as one of the predominant regulators modulating the senescent signature of alveolar macrophages in ACO. Collectively, the findings suggest that senescence in macrophages, particularly alveolar macrophages, plays a crucial role in the pathophysiology of ACO. Furthermore, PPARγ may represent a potential therapeutic target for interventions aimed at modulating senescence-associated processes in ACO.

Machine learning parallel system for integrated process-model calibration and accuracy enhancement in sewer-river system

The process-based water system models have been transitioning from single-functional to integrated multi-objective and multi-functional since the worldwide digital upgrade of urban water system management. The proliferation of model complexity results in more significant uncertainty and computational requirements. However, conventional model calibration methods are insufficient in dealing with extensive computational time and limited monitoring samples. Here we introduce a novel machine learning system designed to expedite parameter optimization with limited data and boost efficiency in parameter search. MLPS, termed the machine learning parallel system for fast parameter search of integrated process-based models, aims to enhance both the performance and efficiency of the integrated model by ensuring its comprehensiveness, accuracy, and stability. MLPS was constructed upon the concept of model surrogation + algorithm optimization using Ant Colony Optimization (ACO) coupled with Long Short-Term Memory (LSTM). The optimization results of the Integrated sewer network and urban river model demonstrate that the average relative percentage difference of the predicted river pollutant concentrations increases from 1.1 to 6.0, and the average absolute percent bias decreases from 124.3% to 8.8%. The model outputs closely align with the monitoring data, and parameter calibration time is reduced by 89.94%. MLPS enables the efficient optimization of integrated process-based models, facilitating the application of highly precise complex models in environmental management. The design of MLPS also presents valuable insights for optimizing complex models in other fields.

The value of bronchodilator response in FEV1 and FeNO for differentiating between chronic respiratory diseases: an observational study

BACKGROUND

There is no uniform standard for a strongly positive bronchodilation test (BDT) result. In addition, the role of bronchodilator response in differentiating between asthma, chronic obstructive pulmonary disease (COPD), and asthma-COPD overlap (ACO) in patients with a positive BDT result is unclear. We explored a simplified standard of a strongly positive BDT result and whether bronchodilator response combined with fractional exhaled nitric oxide (FeNO) can differentiate between asthma, COPD, and ACO in patients with a positive BDT result.

METHODS

Three standards of a strongly positive BDT result, which were, respectively, defined as post-bronchodilator forced expiratory volume in 1-s responses (ΔFEV1) increasing by at least 400 mL + 15% (standard I), 400 mL (standard II), or 15% (standard III), were analyzed in asthma, COPD, and ACO patients with a positive BDT result. Receiver operating characteristic curves were used to determine the optimal values of ΔFEV1 and FeNO. Finally, the accuracy of prediction was verified by a validation study.

RESULTS

The rates of a strongly positive BDT result and the characteristics between standards I and II were consistent; however, those for standard III was different. ΔFEV1 ≥ 345 mL could predict ACO diagnosis in COPD patients with a positive BDT result (area under the curve [AUC]: 0.881; 95% confidence interval [CI] 0.83-0.94), with a sensitivity and specificity of 90.0% and 91.2%, respectively, in the validation study. When ΔFEV1 was < 315 mL combined with FeNO < 28.5 parts per billion, patients with a positive BDT result were more likely to have pure COPD (AUC: 0.774; 95% CI 0.72-0.83).

CONCLUSION

The simplified standard II can replace standard I. ΔFEV1 and FeNO are helpful in differentiating between asthma, COPD, and ACO in patients with a positive BDT result.

Multi class robust brain tumor with hybrid classification using DTA algorithm

Analyzing brain tumours is important for prompt diagnosis and efficient patient care. The morphology of tumours, which includes their size, location, texture, and heteromorphic appearance in medical pictures, makes them difficult to analyse. A unique two-phase deep learning-based framework is suggested in this respect to recognise and classify brain cancers in magnetic resonance images (MRIs). A new DTA approach is suggested in the first phase to successfully identify tumour MRI images from healthy persons. DTA are specifically designed and perform well are used to create the deep boosted feature space, which is then fed into the group of machine learning (ML) classifiers. In the second stage, a brand-new hybrid features fusion-based brain tumour classification technique is put forward, one that makes use of both static and dynamic features as well as an ML classifier to classify various tumour kinds. The proposed algorithm, which can recognise the heteromorphic and variable behaviour of different tumours, is where the dynamic characteristics are taken.In this paper, many segmentation algorithms for MRI and PET are reviewed together with their performance evaluations in order to detect brain tumours. There are numerous segmentation methods available for the diagnosis of medical images. The features of the image, such as the capacity to distinguish between similarities and discontinuities, are often used to classify the segmentation techniques. Neuroradiologists have a difficult issue in trying to quickly identify the abnormal region, which is essential in the medical field. In order to overcome this problem, the efficiency of different segmentation procedures is assessed. The segmentation methods considered here are Ant Colony Optimization (ACO), Wavelet Transform (WT), Gradient Vector Flow (GVF), Gray level Co-occurrence matrix (GLCM), and Artificial Bee Colony (ABC). The various performance metrics are used to evaluate the suggested segmentation algorithms. The GVF strategy works better with MRI images, whereas the ABC and ACO approaches perform similarly with PET scans, according to the data acquired.

Clinical phenotypes of COPD and their impact on quality of life: A cross-sectional study

BACKGROUND

A Chronic Obstructive Pulmonary Disease (COPD) phenotype is a single or group of disease characteristics that describe differences between individuals based on clinically important factors such as symptoms, exacerbations, morbidity, and treatment responses. Many studies estimated the prevalence of various phenotypes, but very few studies looked into their quality of life. We aimed to estimate the prevalence of different COPD phenotypes and their disease-specific Health-Related Quality of Life (HRQoL).

MATERIALS AND METHODS

The prospective study, with a sample size of 136, was conducted between May 2021 and December 2022 in a tertiary teaching institute. Based on their clinical features, COPD patients were classified into 4 different clinical phenotypes, and their disease-specific quality of life was assessed using St. George Respiratory Questionnaire-COPD(SGRQ-c) and COPD Assessment Test (CAT) questionnaires.

RESULTS

Among 136 COPD patients, the frequency of Non-Exacerbator (NE), Exacerbator Emphysema (EEM), Exacerbator Chronic Bronchitis (ECB), and Asthma COPD overlap (ACO) phenotypes was 79(58.1 %), 16(11.8 %), 31(22.8 %), and 10(7.4 %) respectively. Based on the SGRQ-c score, the ECB and EEM phenotypes had a significantly poorer Quality of life (QoL) when compared with NE(P<0.0001), ACO(P=0.011), phenotypes. Similarly, ECB and EEM phenotypes had significantly poorer QoL when compared to NE(P<0.0001), and ACO(P=0.015), based on the CAT score. ECB and EEM patients also had the worst scores in all individual CAT items and SGRQ-c components.

CONCLUSION

NE was the most common followed by ECB phenotype. ECB and EEM phenotypes recorded the poorest quality of life without any significant differences among them. Further research is needed in the future to determine whether phenotype-specific therapies can produce better clinical outcomes.

Picturing asthma in Turkey: results from the Turkish adult asthma registry

INTRODUCTION

National data on asthma characteristics and the factors associated with uncontrolled asthma seem to be necessary for every country. For this purpose, we developed the Turkish Adult Asthma Registry for patients with asthma aiming to take a snapshot of our patients, thereby assigning the unmet needs and niche areas of intervention.

METHODS

Case entries were performed between March 2018 and March 2022. A web-based application was used to record data. Study outcomes were demographic features, disease characteristics, asthma control levels, and phenotypes.

RESULTS

The registry included 2053 patients from 36 study centers in Turkey. Female subjects dominated the group (n = 1535, 74.8%). The majority of the patients had allergic (n = 1158, 65.3%) and eosinophilic (n = 1174, 57.2%) asthma. Six hundred nineteen (32.2%) of the patients had obese asthma. Severe asthma existed in 670 (32.6%) patients. Majority of cases were on step 3-5 treatment (n: 1525; 88.1%). Uncontrolled asthma was associated with low educational level, severe asthma attacks in the last year, low FEV1, existence of chronic rhinosinusitis and living in particular regions.

CONCLUSION

The picture of this registry showed a dominancy of middle-aged obese women with moderate-to-severe asthma. We also determined particular strategic targets such as low educational level, severe asthma attacks, low FEV1, and chronic rhinosinusitis to decrease uncontrolled asthma in our country. Moreover, some regional strategies may also be needed as uncontrolled asthma is higher in certain regions. We believe that these data will guide authorities to reestablish national asthma programs to improve asthma service delivery.

Changes in Health Care Utilization During the First 2 Years of Massachusetts Medicaid Accountable Care Organizations

On March 1, 2018, the Massachusetts Medicaid and Children's Health Insurance Program (MassHealth) launched an ambitious accountable care organization (ACO) program that sought to integrate care across the physical, behavioral, functional, and social services continuum while holding ACOs accountable for cost and quality. The study objective was to describe changes in health care utilization among MassHealth members during the pre-ACO baseline (2015-2017) and post-implementation periods (2018 and 2019). Using MassHealth administrative data, the authors conducted a repeated cross-sectional study of MassHealth members enrolled in ACOs during 2015-2019. Rates of primary care visits, all-cause and primary-care sensitive emergency department (ED) visits, ED boarding, hospitalizations, acute unplanned admissions, and readmissions were reported during the baseline period (2015-2017) and year 1 (2018) and year 2 (2019). Primary care visit rates increased for adult members throughout the study period from a baseline mean of 7.2-9.2 per member per year (observed-to-expected [O:E]: 1.16) in 2019. Observed all-cause hospitalization rates fell below expected values with O:E ratios of 0.96 among adults and 0.79 among children in 2018, and 0.96 and 0.92 among adults and children, respectively, in 2019. All-cause ED visit rates increased slightly, and rates of pediatric asthma-related admissions, unplanned admissions for adults with ambulatory care sensitive conditions, and unplanned admissions and ED boarding for adults with substance use disorder and serious mental illness all declined for the study period. These findings are suggestive of utilization shifts to higher-value, lower-cost care under Massachusetts's innovative and comprehensive ACO model.

Facilitators and Barriers to Care Coordination Between Medicaid Accountable Care Organizations and Community Partners: Early Lessons From Massachusetts

Care coordination is central to health care delivery system reform efforts to control costs, improve quality, and enhance patient outcomes, especially for individuals with complex medical and social needs. The potential impact of addressing health-related social needs further illustrates the importance of coordinating health care services with community-based organizations that provide social services and support. This study offers early findings from a unique approach to care coordination delivered by 17 Medicaid Accountable Care Organizations and 27 partnering community-based organizations for individuals with behavioral health conditions and/or those needing long-term services and supports. Interview data from 54 key informants were qualitatively analyzed to understand factors affecting cross-sector integrated care. Key themes emerged, essential to implementing the new model statewide: clarifying roles and responsibilities; promoting communication; facilitating information exchange; developing workforce capacity; building essential relationships; and responsive, supportive program management through real-time feedback, financial incentives, technical assistance, and flexibility from the state Medicaid program.

Airway inflammatory changes in the lungs of patients with asthma-COPD overlap (ACO): a bronchoscopy endobronchial biopsy study

BACKGROUND

Although asthma and chronic obstructive pulmonary disease (COPD) are two distinct chronic airway inflammatory diseases, they often co-exist in a patient and the condition is referred to as asthma-COPD overlap (ACO). Lack of evidence regarding the inflammatory cells in ACO airways has led to their poor prognosis and treatment. The objective of this endobronchial biopsy (EBB) study was to enumerate inflammatory cellular changes in the airway wall of ACO compared with asthma, COPD current smokers (CS) and ex-smokers (ES), normal lung function smokers (NLFS), and non-smoker controls (HC).

METHODS

EBB tissues from 74 patients were immunohistochemically stained for macrophages, mast cells, eosinophils, neutrophils, CD8+ T-cells and CD4+ T-cells. The microscopic images of stained tissues were evaluated in the epithelium, reticular basement membrane (RBM) cells/mm RBM length, and lamina propria (LP) cells/mm2 up to a depth of 120 µM using the image analysis software Image-Pro Plus 7.0. The observer was blinded to the images and disease diagnosis. Statistical analysis was performed using GraphPad Prism v9.

RESULTS

The tissue macrophages in ACO were substantially higher in the epithelium and RBM than in HC (P < 0.001 for both), COPD-ES (P < 0.001 for both), and -CS (P < 0.05 and < 0.0001, respectively). The ACO LP macrophages were significantly higher in number than COPD-CS (P < 0.05). The mast cell numbers in ACO were lower than in NLFS (P < 0.05) in the epithelium, lower than COPD (P < 0.05) and NLFS (P < 0.001) in RBM; and lower than  HC (P < 0.05) in LP. We noted lower eosinophils in ACO LP than HC (P < 0.05) and the lowest neutrophils in both ACO and asthma. Furthermore, CD8+ T-cell numbers increased in the ACO RBM than HC (P < 0.05), COPD-ES (P < 0.05), and NLFS (P < 0.01); however, they were similar in number in epithelium and LP across groups. CD4+ T-cells remained lower in number across all regions and groups.

CONCLUSION

These results suggest that the ACO airway tissue inflammatory cellular profile differed from the contributing diseases of asthma and COPD with a predominance of macrophages.

A Quality-of-Service-Aware Service Composition Method in the Internet of Things Using a Multi-Objective Fuzzy-Based Hybrid Algorithm

The Internet of Things (IoT) represents a cutting-edge technical domain, encompassing billions of intelligent objects capable of bridging the physical and virtual worlds across various locations. IoT services are responsible for delivering essential functionalities. In this dynamic and interconnected IoT landscape, providing high-quality services is paramount to enhancing user experiences and optimizing system efficiency. Service composition techniques come into play to address user requests in IoT applications, allowing various IoT services to collaborate seamlessly. Considering the resource limitations of IoT devices, they often leverage cloud infrastructures to overcome technological constraints, benefiting from unlimited resources and capabilities. Moreover, the emergence of fog computing has gained prominence, facilitating IoT application processing in edge networks closer to IoT sensors and effectively reducing delays inherent in cloud data centers. In this context, our study proposes a cloud-/fog-based service composition for IoT, introducing a novel fuzzy-based hybrid algorithm. This algorithm ingeniously combines Ant Colony Optimization (ACO) and Artificial Bee Colony (ABC) optimization algorithms, taking into account energy consumption and Quality of Service (QoS) factors during the service selection process. By leveraging this fuzzy-based hybrid algorithm, our approach aims to revolutionize service composition in IoT environments by empowering intelligent decision-making capabilities and ensuring optimal user satisfaction. Our experimental results demonstrate the effectiveness of the proposed strategy in successfully fulfilling service composition requests by identifying suitable services. When compared to recently introduced methods, our hybrid approach yields significant benefits. On average, it reduces energy consumption by 17.11%, enhances availability and reliability by 8.27% and 4.52%, respectively, and improves the average cost by 21.56%.

Effects of a Peptide Derived from the Primary Sequence of a Kallikrein Inhibitor Isolated from Bauhinia bauhinioides (pep-BbKI) in an Asthma-COPD Overlap (ACO) Model

(1) There are several patients with asthma-COPD overlap (ACO). A peptide derived from the primary sequence of a kallikrein inhibitor isolated from Bauhinia bauhinioides (pep-BbKI) has potent anti-inflammatory and antioxidant effects. Purpose: To investigate the effects of pep-BbKI treatment in an ACO model and compare them with those of corticosteroids. (2) BALB/c mice were divided into groups: SAL (saline), OVA (ovalbumin), ELA (elastase), ACO (ovalbumin + elastase), ACO-pep-BbKI (treated with inhibitor), ACO-DX (dexamethasone treatment), ACO-DX-pep-BbKI (both treatments), and SAL-pep-BbKI (saline group treated with inhibitor). We evaluated: hyperresponsiveness to methacholine, bronchoalveolar lavage fluid (BALF), exhaled nitric oxide (eNO), IL-1β, IL-4, IL-5, IL-6, IL-10, IL-13, IL-17, IFN-γ, TNF-α, MMP-9, MMP-12, TGF-β, collagen fibers, iNOS, eNO, linear mean intercept (Lm), and NF-κB in airways (AW) and alveolar septa (AS). (3) ACO-pep-BbKI reversed ACO alterations and was similar to SAL in all mechanical parameters, Lm, neutrophils, IL-5, IL-10, IL-17, IFN-γ, TNF-α, MMP-12 (AW), collagen fibers, iNOS (AW), and eNO (p > 0.05). ACO-DX reversed ACO alterations and was similar to SAL in all mechanical parameters, Lm, total cells and differentials, IL-1β(AS), IL-5 (AS), IL-6 (AS), IL-10 (AS), IL-13 (AS), IFN-γ, MMP-12 (AS), TGF-β (AS), collagen fibers (AW), iNOS, and eNO (p > 0.05). SAL was similar to SAL-pep-BbKI for all comparisons (p > 0.05). (4) Pep-BbKI was similar to dexamethasone in reducing the majority of alterations of this ACO model.

Hybrid Models Based on Fusion Features of a CNN and Handcrafted Features for Accurate Histopathological Image Analysis for Diagnosing Malignant Lymphomas

Malignant lymphoma is one of the most severe types of disease that leads to death as a result of exposure of lymphocytes to malignant tumors. The transformation of cells from indolent B-cell lymphoma to B-cell lymphoma (DBCL) is life-threatening. Biopsies taken from the patient are the gold standard for lymphoma analysis. Glass slides under a microscope are converted into whole slide images (WSI) to be analyzed by AI techniques through biomedical image processing. Because of the multiplicity of types of malignant lymphomas, manual diagnosis by pathologists is difficult, tedious, and subject to disagreement among physicians. The importance of artificial intelligence (AI) in the early diagnosis of malignant lymphoma is significant and has revolutionized the field of oncology. The use of AI in the early diagnosis of malignant lymphoma offers numerous benefits, including improved accuracy, faster diagnosis, and risk stratification. This study developed several strategies based on hybrid systems to analyze histopathological images of malignant lymphomas. For all proposed models, the images and extraction of malignant lymphocytes were optimized by the gradient vector flow (GVF) algorithm. The first strategy for diagnosing malignant lymphoma images relied on a hybrid system between three types of deep learning (DL) networks, XGBoost algorithms, and decision tree (DT) algorithms based on the GVF algorithm. The second strategy for diagnosing malignant lymphoma images was based on fusing the features of the MobileNet-VGG16, VGG16-AlexNet, and MobileNet-AlexNet models and classifying them by XGBoost and DT algorithms based on the ant colony optimization (ACO) algorithm. The color, shape, and texture features, which are called handcrafted features, were extracted by four traditional feature extraction algorithms. Because of the similarity in the biological characteristics of early-stage malignant lymphomas, the features of the fused MobileNet-VGG16, VGG16-AlexNet, and MobileNet-AlexNet models were combined with the handcrafted features and classified by the XGBoost and DT algorithms based on the ACO algorithm. We concluded that the performance of the two networks XGBoost and DT, with fused features between DL networks and handcrafted, achieved the best performance. The XGBoost network based on the fused features of MobileNet-VGG16 and handcrafted features resulted in an AUC of 99.43%, accuracy of 99.8%, precision of 99.77%, sensitivity of 99.7%, and specificity of 99.8%. This highlights the significant role of AI in the early diagnosis of malignant lymphoma, offering improved accuracy, expedited diagnosis, and enhanced risk stratification. This study highlights leveraging AI techniques and biomedical image processing; the analysis of whole slide images (WSI) converted from biopsies allows for improved accuracy, faster diagnosis, and risk stratification. The developed strategies based on hybrid systems, combining deep learning networks, XGBoost and decision tree algorithms, demonstrated promising results in diagnosing malignant lymphoma images. Furthermore, the fusion of handcrafted features with features extracted from DL networks enhanced the performance of the classification models.

A Novelty Procedure to Identify Critical Causes of Materials Incompatibility

Ensuring the expected quality of materials is still a challenge, mainly in order to precisely plan improvement actions that allow for stabilization of the production process. Therefore, the purpose of this research was to develop a novel procedure to identify critical causes of material incompatibility-the causes that have the largest negative impact on material deterioration, and the natural environment. The main originality of this procedure is developing a way to coherent analyse the mutual influence of the many causes of incompatibility of any material, after which the critical causes are identified and a ranking of improvement actions to eliminate these causes is created. A novelty is also developed in the algorithm supporting this procedure, which can be realized in three different ways to solve this problem, i.e.; by considering the impact of material incompatibility on: (i) the deterioration of the material quality; (ii) the deterioration of the natural environment; and (iii) simultaneously the deterioration of the quality of the material and the natural environment. The effectiveness of this procedure was confirmed after tests on 410 alloy, from which a mechanical seal was made. However, this procedure can be useful for any material or industrial product.

Pneumothorax prediction using a foraging and hunting based ant colony optimizer assisted support vector machine

Although PNLB is generally considered safe, it is still invasive and risky. Pneumothorax, the most common complication of lung puncture, can cause shortness of breath, chest pain, and even life-threatening. Therefore, the auxiliary diagnosis for pneumothorax is of great clinical interest. This paper proposes an ant colony optimizer with slime mould foraging behavior and collaborative hunting, called SCACO, in which slime mould foraging behavior is combined to improve the convergence accuracy and solution quality of ACOR. Then the ability of ACO to jump out of the local optimum is optimized by an adaptive collaborative hunting strategy when trapped in the local optimum. As a first step toward Pneumothorax diagnostic prediction, we suggested an SVM classifier based on bSCACO (bSCACO-SVM), which uses the proposed SCACO's binary version as the basis for its feature selection algorithms. To demonstrate the SCACO performance, we first used the slime mould foraging behavior and adaptive cooperative hunting strategy, then compared SCACO with nine basic algorithms and nine variants, respectively. Finally, we verified bSCACO-SVM on various widely used public datasets and applied it to the Pneumothorax prediction issue, showing that it has robust classification prediction capacity and can be successfully employed for tuberculous pleural effusion diagnostic prediction.

Asthma-COPD Overlap in Clinical Practice (ACO_CP 2023): Toward Precision Medicine

Asthma and COPD have characteristic symptoms, yet patients with both are prevalent. Despite this, there is currently no globally accepted definition for the overlap between asthma and COPD, commonly referred to as asthma-COPD overlap (ACO). Generally, ACO is not considered a distinct disease or symptom from either clinical or mechanistic perspectives. However, identifying patients who present with both conditions is crucial for guiding clinical therapy. Similar to asthma and COPD, ACO patients are heterogeneous and presumably have multiple underlying disease processes. The variability of ACO patients led to the establishment of multiple definitions describing the condition's essential clinical, physiological, and molecular characteristics. ACO comprises numerous phenotypes, which affects the optimal medication choice and can serve as a predictor of disease prognosis. Various phenotypes of ACO have been suggested based on host factors including but not limited to demographics, symptoms, spirometric findings, smoking history, and underlying airway inflammation. This review provides a comprehensive clinical guide for ACO patients to be used in clinical practice based on the available limited data. Future longitudinal studies must evaluate the stability of ACO phenotypes over time and explore their predictive powers to facilitate a more precise and effective management approach.

Enhanced QoS Routing Protocol for an Unmanned Ground Vehicle, Based on the ACO Approach

Improving models for managing the networks of firefighting unmanned ground vehicles in crowded areas, as a recommendation system (RS), represented a difficult challenge. This challenge comes from the peculiarities of these types of networks. These networks are distinguished by the network coverage area size, frequent network connection failures, and quick network structure changes. The research aims to improve the communication network of self-driving firefighting unmanned ground vehicles by determining the best routing track to the desired fire area. The suggested new model intends to improve the RS regarding the optimum tracking route for firefighting unmanned ground vehicles by employing the ant colony optimization technique. This optimization method represents one of the swarm theories utilized in vehicles ad-hoc networks and social networks. According to the results, the proposed model can enhance the navigation of self-driving firefighting unmanned ground vehicles towards the fire region, allowing firefighting unmanned ground vehicles to take the shortest routes possible, while avoiding closed roads and traffic accidents. This study aids in the control and management of ad-hoc vehicle networks, vehicles of everything, and the internet of things.

Heterogeneity of asthma-chronic obstructive pulmonary disease (COPD) overlap from a cohort of patients with severe asthma and COPD

BACKGROUND

A considerable proportion of patients have features of both asthma and chronic obstructive pulmonary disease (COPD) simultaneously, called asthma-COPD overlap (ACO).

OBJECTIVES

The aim of this study was to identify heterogeneity of ACO from a cohort of patients with severe asthma and COPD using the same diagnostic criteria.

DESIGN

We used the International Severe Asthma Registry (ISAR) and the Korean COPD Subgroup Study (KOCOSS) to evaluate clinical characteristics of ACO from each cohort.

METHODS

We classified subjects into four groups: (1) pure severe asthma, (2) ACO from the severe asthma cohort, (3) ACO from the COPD cohort, and (4) pure COPD. ACO was defined by satisfying extreme bronchodilator response (BDR) >15% and 400 ml and/or blood eosinophil count ⩾300 /µL in patients aged 40 years or older and post-BD forced expiratory volume in 1 s (FEV₁)/forced vital capacity (FVC) ratio <0.7.

RESULTS

The ACO group had 25 (23%) of 111 in the ISAR cohort and 403 (23%) of 1781 in the KOCOSS cohort. The ACO from the COPD cohort was older with more males and more smokers, but had similar degree of airflow limitation compared with the ACO from the severe asthma cohort. ICS-containing inhaler treatment was prescribed for all severe asthma subjects, but only for 43.9% of ACO subjects from the COPD cohort. Compared with patients having pure severe asthma, the risk for exacerbation was comparable in ACO either from severe asthma or COPD cohort [adjusted odds ratio (aOR): 1.54, 95% CI: 0.22-10.95 or aOR: 2.15, 95% CI: 0.59-7.85].

CONCLUSION

The prevalence of ACO was similar in severe asthma and COPD cohorts applying identical diagnostic criteria. ACO from the severe asthma cohort was similar to ACO from the COPD cohort in terms of lung function and exacerbation risk.

WRKY29 transcription factor regulates ethylene biosynthesis and response in arabidopsis

The gaseous phytohormone ethylene participates in a lot of physiological processes in plants. 1-aminocyclopropane-1-carboxylic acid (ACC) synthase (ACS, EC 4.4.1.14) and the ACC oxidase (ACO, EC 1.14.17.4) are key enzymes in ethylene biosynthesis. However, how ACSs and ACOs are regulated at the transcriptional level is largely unknown. In the present study, we showed that an Arabidopsis (Arabidopsis thaliana) WRKY-type transcription factor (TF), WRKY29 positively regulated the expression of ACS5, ACS6, ACS8, ACS11 and ACO5 genes and thus promoted basal ethylene production. WRKY29 protein was localized in nuclei and was a transcriptional activator. Overexpression of WRKY29 caused pleiotropic effect on plant growth, development and showed obvious response even without ACC treatment. Inducible overexpression of WRKY29 also reduced primary root elongation and lateral root growth. A triple response assay of overexpression and mutant seedlings of WRKY29 showed that overexpression seedlings had shorter hypocotyls than the transgenic GFP (Green Fluorescence Protein) control, while mutants had no difference from wild-type. A qRT-PCR assay demonstrated that expression of multiple ACSs and ACO5 was up-regulated in WRKY29 overexpression plants. A transactivation assay through dual luciferase reporter system confirmed the regulation of promoters of ACS5, ACS6, ACS8, ACS11 and ACO5 by WRKY29. Both in vivo chromatin immunoprecipitation (ChIP)- quantitative PCR and in vitro electrophoretic mobility shift assay (EMSA) revealed that WRKY29 directly bound to the promoter regions of its target genes. Taken together, these results suggest that WRKY29 is a novel TF positively regulating ethylene production by modulating the expression of ACS and ACO genes.

Functional Predictors Discriminating Asthma-COPD Overlap (ACO) from Chronic Obstructive Pulmonary Disease (COPD)

Background

A significant proportion of patients with obstructive lung disease have clinical and functional features of both asthma and chronic obstructive pulmonary disease (COPD), referred to as the asthma–COPD overlap (ACO). The distinction of these phenotypes, however, is not yet well-established due to the lack of defining clinical and/or functional criteria. The aim of our investigations was to assess the discriminating power of various lung function parameters on the assessment of ACO.

Methods

From databases of 4 pulmonary centers, a total of 540 patients (231 males, 309 females), including 372 patients with asthma, 77 patients with ACO and 91 patients with COPD, were retrospectively collected, and gradients among combinations of explanatory variables of spirometric (FEV₁, FEV₁/FVC, FEF_25-75), plethysmographic (sR_eff, sG_eff, the aerodynamic work of breathing at rest; sWOB), static lung volumes, including trapped gases and measurements of the carbon monoxide transfer (DL_CO, K_CO) were explored using multiple factor analysis (MFA). The discriminating power of lung function parameters with respect to ACO was assessed using linear discriminant analysis (LDA).

Results

LDA revealed that parameters of airway dynamics (sWOB, sR_eff, sG_eff) combined with parameters of static lung volumes such as functional residual capacity (FRC_pleth) and trapped gas at FRC (V_TG^FRC) are valuable and potentially important tools discriminating between asthma, ACO and COPD. Moreover, sWOB significantly contributes to the diagnosis of obstructive airway diseases, independent from the state of pulmonary hyperinflation, whilst the diffusion capacity for carbon monoxide (DL_CO) significantly differentiates between the 3 diagnostic classes.

Conclusion

The complexity of COPD with its components of interaction and their heterogeneity, especially in discrimination from ACO, may well be differentiated if patients are explored by a whole set of target parameters evaluating, interactionally, flow limitation, airway dynamics, pulmonary hyperinflation, small airways dysfunction and gas exchange disturbances assessing specific functional deficits.

ACO Spending and Utilization Among Medicare Patients at the End of Life: an Observational Study

BACKGROUND

End-of-life (EOL) costs constitute a substantial portion of healthcare spending in the USA and have been increasing. ACOs may offer an opportunity to improve quality and curtail EOL spending.

OBJECTIVE

To examine whether practices that became ACOs altered spending and utilization at the EOL.

DESIGN

Retrospective analysis of Medicare claims.

PATIENTS

We assigned patients who died in 2012 and 2015 to an ACO or non-ACO practice. Practices that converted to ACOs in 2013 or 2014 were matched to non-ACOs in the same region. A total of 23,643 ACO patients were matched to 23,643 non-ACO patients.

MAIN MEASURES

Using a difference-in-differences model, we examined changes in EOL spending and care utilization after ACO implementation.

KEY RESULTS

The introduction of ACOs did not significantly impact overall spending for patients in the last 6 months of life (difference-in-difference (DID) = $192, 95%CI -$841 to $1125, P = 0.72). Changes in spending did not differ between ACO and non-ACO patients across spending categories (inpatient, outpatient, physician services, skilled nursing, home health, hospice). No differences were seen between ACO and non-ACO patients in rates of ED visits, inpatient admissions, ICU admission, mean healthy days at home, and mean hospice days at 180 and 30 days prior to death. However, non-ACO patients had a significantly greater increase in hospice utilization compared to ACO patients at 180 days (DID P-value = 0.02) and 30 days (DID P-value = 0.01) prior to death.

CONCLUSIONS

With the exception of hospice care utilization, spending and utilization were not different between ACOs and non-ACO patients at the EOL. Longer follow-up may be necessary to evaluate the impact of ACOs on EOL spending and care.

Differential airway remodelling changes were observed in patients with asthma COPD overlap (ACO) compared to asthma and COPD patients alone

Management of patients with asthma COPD overlap (ACO) is clinically challenging due to insufficient evidence of pathological changes in these patients. In this cross-sectional study, we evaluated airway remodeling in endobronchial biopsies from a total of 90 subjects, which included 12 ACO, 14 patients with asthma, 12 COPD exsmokers (ES), 11 current smokers (CS), 28 healthy controls (HC), and 13 normal lung function smokers (NLFS). Tissue was stained with Masson’s trichrome. Epithelium, goblet cells, reticular basement membrane (RBM), cellularity, lamina propria (LP), and smooth muscle (SM) changes were measured using Image-Pro Plus v7 software. Differential airway remodeling pattern was seen in patients with ACO. A limited change was noted in the ACO epithelium compared with other pathological groups. RBM was substantially thicker in patients with ACO than in HC (P < 0.0002) and tended to be thicker than in patients with asthma and NLFS. The total RBM cells were higher in ACO than in the HC (P < 0.0001), COPD-CS (P = 0.0559), -ES (P = 0.0345), and NLFS (P < 0.0002), but did not differ from patients with asthma. Goblet cells were higher in the ACO than in the HC (P = 0.0028) and COPD-ES (P = 0.0081). The total LP cells in ACO appeared to be higher than in HC, COPD-CS, and NLFS but appeared to be lower than in patients with asthma. Finally, SM area was significantly lower in the ACO than in patients with asthma (P = 0.001), COPD-CS (=0.0290), and NLFS (P = 0.0011). This first comprehensive study suggests that patients with ACO had distinguishable tissue remodeling that appeared to be more severe than patients with asthma and COPD. This study will help in informed decision-making for better patient management in clinical practice.

Early Features of Chronic Obstructive Pulmonary Disease in Patients with Asthma: Is there ACO before ACO?

The diagnosis of asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) is considered when a patient presents features of both asthma and COPD, usually including a component of irreversible airway obstruction (IRAO). However, some patients with asthma, particularly smokers, may have various features typical of COPD in the absence of such component of IRAO. Features of early COPD can be found at a young age in such patients even with normal spirometry. More longitudinal studies should be conducted to determine steps needed to improve clinical outcomes of these patients including the early recognition of these changes and the application of preventative/therapeutic interventions.

Defining Asthma-Chronic Obstructive Pulmonary Disease Overlap

Much interest has been given to the asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) in the past 2 decades, but the condition is still ill-defined. There is general agreement that a patient with longstanding asthma who develops fixed airflow obstruction after years of smoking has ACO although defining asthma in the face of COPD can be challenging. Many features of asthma are also found in patients with COPD without indicating an overlap and no consensus exists on which characteristics should be included in the definition of ACO. Nevertheless, some guidance has been issued to help clinicians and researchers to make a diagnosis of ACO and these will be reviewed here.

Directional mutation and crossover boosted ant colony optimization with application to COVID-19 X-ray image segmentation

This paper focuses on the study of Coronavirus Disease 2019 (COVID-19) X-ray image segmentation technology. We present a new multilevel image segmentation method based on the swarm intelligence algorithm (SIA) to enhance the image segmentation of COVID-19 X-rays. This paper first introduces an improved ant colony optimization algorithm, and later details the directional crossover (DX) and directional mutation (DM) strategy, XMACO. The DX strategy improves the quality of the population search, which enhances the convergence speed of the algorithm. The DM strategy increases the diversity of the population to jump out of the local optima (LO). Furthermore, we design the image segmentation model (MIS-XMACO) by incorporating two-dimensional (2D) histograms, 2D Kapur's entropy, and a nonlocal mean strategy, and we apply this model to COVID-19 X-ray image segmentation. Benchmark function experiments based on the IEEE CEC2014 and IEEE CEC2017 function sets demonstrate that XMACO has a faster convergence speed and higher convergence accuracy than competing models, and it can avoid falling into LO. Other SIAs and image segmentation models were used to ensure the validity of the experiments. The proposed MIS-XMACO model shows more stable and superior segmentation results than other models at different threshold levels by analyzing the experimental results.

Medicare accountable care organizations: post-acute care use and post-surgical outcomes in urologic cancer surgery

OBJECTIVES

To evaluate association between Medicare accountable care organizations (ACOs) participation of hospitals on post-acute care (PAC) use and spending, and post-surgical outcomes in Medicare beneficiaries undergoing urologic cancer surgeries. Despite increasing prevalence of urologic cancer and surgical care contributing to a large proportion of total health care costs, and recent Medicare payment reforms such as accountable care organizations, the role of ACOs in urologic cancer care has been unexplored.

METHODS

We conducted a longitudinal analysis of 2011-2017 Medicare claims data to compare post-surgical outcomes between Medicare ACO and non-ACO patients before and after implementation of Medicare shared savings program (MSSP). Our outcomes of interest were Post-acute care (PAC) use (overall, institutional, and home health), Skilled Nursing Facility (SNF) length of stay and Medicare spending for SNF patients, 30-day and 90-day unplanned readmissions and complications after index procedure.

RESULTS

Study sample included a total of 334,514 Medicare patients undergoing bladder, prostate, kidney cancer surgeries at 524 Medicare ACO and 2066 non-ACO hospitals. For bladder cancer surgery, Medicare ACO participation was associated with significantly reduced overall post-acute care use, but not with changes in readmission or complication rate. For prostate cancer and kidney cancer surgery, we found no significant association between hospital participation in Medicare ACOs and PAC use or post-surgical outcomes.

CONCLUSIONS

Hospital participation in MSSP ACOs leads to lower post-acute care use without compromising patient outcomes for Medicare beneficiaries undergoing bladder cancer surgery. Future research is needed to understand longer-term impact of ACO participation on urologic cancer surgery outcomes.

Ultra-Low Oxygen and Preconditioning Storage Regulate Ethylene Synthesis to Prevent Corky Disorders in 'Fuji' Apple

Corky disorders in apples represent a significant problem for long-term storage where controlled atmosphere (CA) is mainly used. Ultra-low oxygen (ULO) is an alternative to CA, which consists of low partial pressure of O₂ to maintain a low metabolism in the apple fruit, achieving an effective decrease in the ethylene production and physiological disorders. The aim of this research was to study the effectiveness of a short hypoxia period on the development of cork physiological disorders during the storage of apple. 'Fuji' apples were prestored under ULO (0.5 kPa O₂) for two periods of time (15 and 30 days) and at two temperatures (0 or 5^°C). Corky physiological disorders increased at 5^°C prestorage temperature; however, ULO treatments for 15 or 30 days at 0 or 5^°C achieved a significant reduction in corky disorders near to 1%, compared with control treatments. In addition, a considerable reduction in ethylene production for up to 30 days was observed in ULO-treated fruit at 0 and 5^°C. ULO for 30 days at 0 and 5^°C increased the internal production of ethanol and acetaldehyde, causing a lower sensory quality due to the presence of fermentative flavors in fruit stored at 5^°C. ULO of 15 days of conditioning decreased the relative expression of ethylene biosynthesis genes MdACS1 and MdACO1, resulting in lower ethylene production.

Market and Organizational Factors Associated with Hospital Leadership of Accountable Care Organizations

BACKGROUND

The number of Accountable Care Organizations (ACOs) in the U.S. has been rapidly increasing during the past decade. Despite the growth of Accountable Care Organizations (ACOs), little is known about the factors that are associated with hospital leadership of ACOs that contract with public and private payers.

PURPOSE

Using a resource dependency framework, this study examines the organizational characteristics and environmental factors that are associated with hospitals who are leading an ACO.

METHODOLOGY

We used the data from the American Hospital Association (AHA) Annual Survey of Hospitals for 2018, the Area Health Resources Files and the Medicare Cost Reports. A multiple logistic regression was used to test associations of the independent variables with the hospital leadership of ACOs.

RESULTS

We found that nearly one third of the hospitals studied were leading an ACO. System affiliated and not-for-profit hospitals were more likely to be the leaders. Hospitals that lead an ACO offer more clinical services and have better financial performance. Metropolitan core-based statistical areas and per capita income were significantly positively associated with leading an ACO. However, the proportion of population aged 65 and over and the percentage of Medicare advantage penetration were significantly negatively associated with leading an ACO.

CONCLUSIONS

Hospitals vary in leading an ACO, which may provide critical resources for them by creating an infrastructure that enables accountable care, extends their services into population health and value-based care programs increasingly promoted by public and commercial payers.

Crosstalk Between Ethylene and Abscisic Acid During Changes in Soil Water Content Reveals a New Role for 1-Aminocyclopropane-1- Carboxylate in Coffee Anthesis Regulation

Coffee (Coffea arabica L.) presents an asynchronous flowering regulated by an endogenous and environmental stimulus, and anthesis occurs once plants are rehydrated after a period of water deficit. We evaluated the evolution of Abscisic Acid (ABA), ethylene, 1-aminocyclopropane-1-carboxylate (ACC) content, ACC oxidase (ACO) activity, and expression analysis of the Lysine Histidine Transporter 1 (LHT1) transporter, in the roots, leaves, and flower buds from three coffee genotypes (C. arabica L. cv Oeiras, Acauã, and Semperflorens) cultivated under field conditions with two experiments. In a third field experiment, the effect of the exogenous supply of ACC in coffee anthesis was evaluated. We found an increased ACC level, low ACO activity, decreased level of ethylene, and a decreased level of ABA in all tissues from the three coffee genotypes in the re-watering period just before anthesis, and a high expression of the LHT1 in flower buds and leaves. The ethylene content and ACO activity decreased from rainy to dry period whereas the ABA content increased. A higher number of opened and G6 stage flower buds were observed in the treatment with exogenous ACC. The results showed that the interaction of ABA-ACO-ethylene and intercellular ACC transport among the leaves, buds, and roots in coffee favors an increased level of ACC that is most likely, involved as a modulator in coffee anthesis. This study provides evidence that ACC can play an important role independently of ethylene in the anthesis process in a perennial crop.

Clinical Implications of Bronchodilator Testing: Diagnosing and Differentiating COPD and Asthma-COPD Overlap

BACKGROUND

Bronchodilation testing is an important component of spirometry testing, and omitting this procedure has potential clinical implications toward diagnosing respiratory diseases. We aimed to estimate the impact of bronchodilator testing in accurately diagnosing COPD and differentiating COPD from asthma-COPD overlap (ACO).

METHODS

The National Health and Nutrition Examination Survey data were analyzed from 2007-2012. Airflow limitation was defined by FEV₁/FVC < 0.7. Subjects with pre-bronchodilator airflow limitation were classified into pre-but-not-post-bronchodilator airflow limitation and post-bronchodilator airflow limitation groups. Spirometry-confirmed COPD was defined by persistent airflow limitation on post-bronchodilator spirometry. The American Thoracic Society (ATS) and the Spanish Society of Pneumology and Thoracic Surgery (SEPAR) definitions were used to identify possible ACO subjects.

RESULTS

We identified 11,763 subjects ≥ 40 y of age eligible for spirometry; 625 of them had a pre-bronchodilator FEV₁/FVC < 0.7 and completed post-bronchodilator spirometry that met ATS spirometry quality standards. A total of 244 (39%) of these subjects had only pre-not-post-bronchodilator airflow limitation, thereby not meeting the definition of spirometrically confirmed COPD. The prevalence of ACO was 7.6% using the modified ATS definition and 19.8% using the modified SEPAR criteria. When bronchodilator testing-based criteria were excluded from ATS and SEPAR definitions, the number of ACO subjects decreased by 39.3% and 12.3%, respectively.

CONCLUSIONS

Spirometry with bronchodilation is an important element in the accurate diagnosis of ACO and COPD. Spirometry performed without bronchodilator testing may lead to an estimated misclassification of ACO by 7.6% to 19.8% and overdiagnosis of COPD by 39%.

The effectiveness of short-term pulmonary rehabilitation program in patients with comorbid asthma, chronic obstructive pulmonary disease and obesity

The effectiveness of pulmonary rehabilitation (PR) has not yet been established in patients with asthma – chronic obstructive pulmonary disease overlap (ACO) depending on their nutritional status. We aimed to evaluate the effectiveness of a short-term PR program in patients with comorbid asthma, chronic obstructive pulmonary disease (COPD), and obesity. We included 40 ACO patients and divided them into 3 groups according to body mass index (BMI) and then subdivided them into PR (n=21) and control (n=19) groups. The COPD Assessment Test (CAT), the Asthma Control Test (ACT), and the modified Medical Research Council dyspnea scale (mMRS) were used to evaluate symptoms levels. BODE index (body mass index, forced expiratory volume in one second, dyspnoea, and 6-min walk distance) was used to evaluate the effectiveness of pulmonary rehabilitation. In addition, spirometry and bioimpedansometry were performed. All measurements were done before and after a 6-month PR program. A significantly lower decline in the BODE index was observed in overweight patients (decreased by 43.6% compared to baseline and lower by 40.7% compared to the control group). The six-minute walking test (6MWT) significantly increased in all groups (p<0.001). There was a decrease in total CAT score by 25.4% and by 31.2% in the overweight group (p<0.001). The BMI decreased more in the obese group (by 9.4% compared to baseline). Our study result showed that early use of PR program significantly improves functional capacity and BODE index, leads to dyspnea and CAT scores reduction and improvement in pulmonary function, cause a decrease in BMI, body fat percentage, and visceral fat level, and an increase in muscle mass in overweight and obese patients with ACO.

Transition Zone1 Negatively Regulates Arabidopsis Aluminum Resistance Through Interaction With Aconitases

The soluble form of aluminum (Al) is a major constraint to crop production in acidic soils. The Al exclusion correlated with the Al-induced organic acid is considered as an important mechanism of Al resistance. The regulation of organic acid exudation in response to Al stress mediated by the root organic acid transporters has been extensively studied. However, how plants respond to Al stress through the regulation of organic acid homeostasis is not well understood. In this study, we identified the functionally unknown Transition zone1 (TZ1) as an Al-inducible gene in the root transition zone, the most sensitive region to Al stress, in Arabidopsis. tz1 mutants showed enhanced Al resistance and displayed greatly reduced root growth inhibition. Furthermore, TZ1 was found to interact with the aconitases (ACOs) which can catalyze the conversion from citrate, one of the most important organic acids, into isocitrate. Consistently, in tz1 mutants, the citric acid content was highly increased. Collectively, this study provides evidence to show that TZ1 negatively regulates root growth response to Al stress through interacting with ACOs and regulating citric acid homeostasis.

Respiratory-related death in individuals with incident asthma and COPD: a competing risk analysis

Background

Distinguishing between mortality attributed to respiratory causes and other causes among people with asthma, COPD, and asthma-COPD overlap (ACO) is important. This study used electronic health records in England to estimate excess risk of death from respiratory-related causes after accounting for other causes of death.

Methods

We used linked Clinical Practice Research Datalink (CPRD) primary care and Office for National Statistics mortality data to identify adults with asthma and COPD from 2005 to 2015. Causes of death were ascertained using death certificates. Hazard ratios (HR) and excess risk of death were estimated using Fine-Gray competing risk models and adjusting for age, sex, smoking status, body mass index and socioeconomic status.

Results

65,021 people with asthma and 45,649 with COPD in the CPRD dataset were frequency matched 5:1 with people without the disease on age, sex and general practice. Only 14 in 100,000 people with asthma are predicted to experience a respiratory-related death up to 10 years post-diagnosis, whereas in COPD this is 98 in 100,000. Asthma is associated with an 0.01% excess incidence of respiratory related mortality whereas COPD is associated with an 0.07% excess. Among people with asthma-COPD overlap (N = 22,145) we observed an increased risk of respiratory-related death compared to those with asthma alone (HR = 1.30; 95% CI 1.21–1.40) but not COPD alone (HR = 0.89; 95% CI 0.83–0.94).

Conclusions

Asthma and COPD are associated with an increased risk of respiratory-related death after accounting for other causes; however, diagnosis of COPD carries a much higher probability. ACO is associated with a lower risk compared to COPD alone but higher risk compared to asthma alone.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-01823-4.

Hybrid state analysis with improved firefly optimized linear congestion models of WSNs for DDOS & CRA attacks

A decentralized form represents a wireless network that facilitates the computers to direct communication without any router. The mobility of individual nodes is necessary within the restricted radio spectrum where contact is often possible on an Adhoc basis. The routing protocol must face the critical situation in these networks forwarding exploration between communicating nodes may create the latency problem in the future. The assault is one of the issues has direct impact network efficiency by disseminating false messages or altering routing detail. Hence, an enhanced routing approach proposes to defend against such challenges. The efficiency of the designated model of wireless devices relies on various output parameters to ensure the requirements. The high energy efficient algorithms: LEACH with FUZZY LOGIC, GENETIC, and FIREFLY are the most effective in optimizing scenarios. The firefly algorithm applies in a model of hybrid state logic with energy parameters: data percentage, transmission rate, and real-time application where the architecture methodology needs to incorporate the design requirements for the attacks within the specified network environment, which can affect energy and packet distribution under various system parametric circumstances. These representations can determine with the statistical linear congestion model in a wireless sensor network mixed state environment.

Racial Differences in Prevalence and Clinical Characteristics of Asthma-Chronic Obstructive Pulmonary Disease Overlap

Background: This study examined the differences in the prevalence and clinical features of asthma–chronic obstructive pulmonary disease (COPD) overlap (ACO) with identical diagnostic criteria by race and ethnicity in two nationwide cohorts of COPD.

Methods: We used data from the Korean COPD Subgroup Study (KOCOSS) and phase I of the US Genetic Epidemiology of COPD (COPDGene) study. We defined ACO by satisfying bronchodilator response (BDR) >15% and 400 ml and/or blood eosinophil count ≥300/μl.

Results: The prevalences of ACO according to ethnicity were non-Hispanic white (NHW), 21.4%; African American (AA), 17.4%; and Asian, 23.8%. Asian patients with ACO were older, predominantly male, with fewer symptoms, more severe airflow limitation, and fewer comorbidities than NHW and AA patients. During 1-year follow-up, exacerbations occurred in 28.2, 22.0, and 48.4% of NHW, AA, and Asian patients with ACO, respectively. Compared to patients with non-ACO from the same racial group, the risk for exacerbation was significantly higher in NHW and Asian patients with ACO [adjusted incident rate ratio (aIRR), 1.17; 95% CI, 1.01–1.36, and aIRR, 1.37; 95% CI, 1.09–1.71 for NHW and Asian patients with ACO, respectively]. Inhaled corticosteroid (ICS) reduced the risk for future exacerbation in total patients with ACO but the effect was not significant in each racial group.

Conclusions: The prevalence of ACO was similar in the two cohorts using the same diagnostic criteria. The risk for future exacerbation was significantly higher in ACO, and the use of ICS reduced the risk for exacerbation in total patients with ACO.

Diagnostic value of fractional exhaled nitric oxide in differentiating the asthma-COPD overlap from COPD: a systematic review and meta-analysis

BACKGROUND

Patients with asthma-COPD overlap (ACO) account for 15-20% of chronic obstructive pulmonary disease (COPD), and the incidence increases with age. Patients with ACO have worse outcomes without proper treatment than those with COPD alone. However, the current diagnostic criteria of ACO are mainly based on symptom features and lack of objective indicators. Recently, several studies have demonstrated that fractional exhaled nitric oxide (FeNO) was higher in ACO than in COPD alone. Thus, this study aims to determine the diagnostic value of FeNO in differentiating ACO from COPD and assisting clinical decision-making.

METHODS

We conducted searches in the databases including PubMed, Web of Science, Cochrane Library, and Embase to extract original studies.

RESULTS

In all, 10 studies involving 1335 participants were included in this meta-analysis. FeNO level was significantly higher in ACO patients than in patients with COPD alone (WMD = 11.15ppb, 95%CI = 9.01‒13.28; I² = 18.0%, p = 0.000). The sensitivity and specificity of FeNO in distinguishing ACO from COPD were both 0.71, and the area under the receiver-operating characteristic curve (AUC) was 0.76, indicating that FeNO has moderate diagnostic accuracy in differentiating ACO from COPD.

CONCLUSION

FeNO as an inflammatory biomarker is effective in differentiating ACO from COPD and assisting in clinical decision-making.

New Payment Models: The Medicare Access and CHIP Reauthorization Act of 2015, Merit-based Incentive Payment System, Advanced Alternative Payment Models, Bundling, Value-Based Care, Quadruple Aim, and Big Data: What Do They Mean for Otolaryngology?

New payment models have been introduced by the Centers for Medicare and Medicaid Services to move medicine away from volume-based care toward value-based care. Most models focus on changes for primary care, but specialists like otolaryngologists are wise to familiarize themselves with this changing payment landscape to take advantage of the opportunities and avoid the pitfalls associated with each model.

GenACO a multi-objective cached data offloading optimization based on genetic algorithm and ant colony optimization

BACKGROUND

Data exchange and management have been observed to be improving with the rapid growth of 5G technology, edge computing, and the Internet of Things (IoT). Moreover, edge computing is expected to quickly serve extensive and massive data requests despite its limited storage capacity. Such a situation needs data caching and offloading capabilities for proper distribution to users. These capabilities also need to be optimized due to the experience constraints, such as data priority determination, limited storage, and execution time.

METHODS

We proposed a novel framework called Genetic and Ant Colony Optimization (GenACO) to improve the performance of the cached data optimization implemented in previous research by providing a more optimum objective function value. GenACO improves the solution selection probability mechanism to ensure a more reliable balancing of the exploration and exploitation process involved in finding solutions. Moreover, the GenACO has two modes: cyclic and non-cyclic, confirmed to have the ability to increase the optimal cached data solution, improve average solution quality, and reduce the total time consumption from the previous research results.

RESULT

The experimental results demonstrated that the proposed GenACO outperformed the previous work by minimizing the objective function of cached data optimization from 0.4374 to 0.4350 and reducing the time consumption by up to 47%.

Bronchodilator Response in Patients with COPD, Asthma-COPD-Overlap (ACO) and Asthma, Evaluated by Plethysmographic and Spirometric z-Score Target Parameters

BACKGROUND

Airflow reversibility criteria in COPD are still debated - especially in situations of co-existing COPD and asthma. Bronchodilator response (BDR) is usually assessed by spirometric parameters. Changes assessed by plethysmographic parameters such as the effective, specific airway conductance (sGeff), and changes in end-expiratory resting level at functional residual capacity (FRCpleth) are rarely appreciated. We aimed to assess BDR by spirometric and concomitantly measured plethysmographic parameters. Moreover, BDR on the specific aerodynamic work of breathing (sWOB) was evaluated.

METHODS

From databases of 3 pulmonary centers, BDR to 200 g salbutamol was retrospectively evaluated by spirometric (∆FEV1 and ∆FEF25-75), and plethysmographic (∆sGeff, ∆FRCpleth, and ∆sWOB) parameters in a total of 843 patients diagnosed as COPD (478 = 57%), asthma-COPD-overlap (ACO) (139 = 17%), or asthma (226 = 27%), encountering 1686 BDR-measurement-sets (COPD n = 958; ACO n = 276; asthma n = 452).

RESULTS

Evaluating z-score improvement taking into consideration the whole pre-test z-score range, highest BDR was achieved by combining ∆sGeff and ∆FRC detecting BDR in 62.2% (asthma: 71.4%; ACO: 56.7%; COPD: 59.8%), by ∆sGeff in 53.4% (asthma: 69.1%; ACO: 51.6%; COPD: 47.4%), whereas ∆FEV1 only distinguished in 10.6% (asthma: 21.8%; ACO: 18.6%; COPD: 4.2%). Remarkably, ∆sWOB detected BDR in 49.4% (asthma: 76.2%; ACO: 47.8%; COPD: 46.9%).

CONCLUSION

BDR largely depends on the pre-test functional severity and, therefore, should be evaluated in relation to the pre-test conditions expressed as ∆z-scores, considering changes in airway dynamics, changes in static lung volumes and changes in small airway function. Plethysmographic parameters demonstrated BDR at a significant higher rate than spirometric parameters.

Accurate detection of COVID-19 using deep features based on X-Ray images and feature selection methods

COVID-19 is a severe epidemic affecting the whole world. This epidemic, which has a high mortality rate, affects the health systems and the economies of countries significantly. Therefore, ending the epidemic is one of the most important priorities of all states. For this, automatic diagnosis and detection systems are very important to control the epidemic. In addition to the recommendation of the “reverse transcription-polymerase chain reaction (RT-PCR)” test, additional diagnosis and detection systems are required. Hence, based on the fact that the COVID-19 virus attacks the lungs, automatic diagnosis and detection systems developed using X-ray and CT images come to the fore. In this study, a high-performance detection system was implemented with three different CNN (ResNet50, ResNet101, InceptionResNetV2) models and X-ray images of three different classes (COVID-19, Normal, Pneumonia). The particle swarm optimization (PSO) algorithm and ant colony algorithm (ACO) was applied among the feature selection methods, and their performances were compared. The results were obtained using support vector machines (SVM) and a k-nearest neighbor (k-NN) classifier using the 10-fold cross-validation method. The highest overall accuracy performance was 99.83% with the SVM algorithm without feature selection. The highest performance was achieved after the feature selection process with the SVM + PSO method as 99.86%. As a result, higher performance with less computational load has been achieved by realizing the feature selection. Based on the high results obtained, it is thought that this study will benefit radiologists as a decision support system.

A Prospective Cohort Study to Assess Obstructive Respiratory Disease Phenotypes and Endotypes in Japan: The TRAIT Study Design

Background

Asthma, chronic obstructive pulmonary disease (COPD), and asthma-COPD overlap (ACO) are complex and heterogeneous diseases that share clinical characteristics (phenotypes) and molecular mechanisms (endotypes). Whilst physicians make clinical decisions on diagnostic groups, for some such as ACO there is no commonly accepted criteria. An alternative approach is to evaluate phenotypes and endotypes that are considered to respond well to a specific type of treatment ("treatable traits") rather than diagnostic labels.

Purpose

The prospective, longitudinal, and observational TRAIT study will evaluate disease characteristics, including both phenotypes and endotypes, in relation to the presentation of obstructive respiratory disease characteristics in patients diagnosed with asthma, COPD, or ACO in Japan, with the aim of further understanding the clinical benefit of a treatable traits-based approach.

Patients and Methods

A total of 1500 participants will be enrolled into three cohorts according to their treating physician's diagnosis of asthma, COPD, or ACO at screening. Part 1 of the study will involve cross-sectional phenotyping and endotyping at study enrollment. Part 2 of the study will evaluate the progression of clinical characteristics, biomarker profiles, and treatment over a 3-year follow-up period. The follow-up will involve three annual study visits and three telephone calls scheduled at 6-month intervals. A substudy involving 50 participants from the asthma cohort (in which the ratio will be approximately 1:1 including 25 participants with a smoking history of ≥10 pack-years and 25 participants with no smoking history), 100 participants from the ACO cohort, and 100 participants from the COPD cohort will evaluate disease phenotypes using inspiratory and expiratory computed tomography scans.

Conclusion

TRAIT will describe clinical characteristics of patients with obstructive respiratory diseases to better understand potential differences and similarities between clinical diagnoses, which will support the improvement of personalized treatment strategies.

Update on Asthma-COPD Overlap (ACO): A Narrative Review

Although chronic obstructive pulmonary disease (COPD) and asthma are well-characterized diseases, they can coexist in a given patient. The term asthma-COPD overlap (ACO) was introduced to describe patients that have clinical features of both diseases and may represent around 25% of COPD patients and around 20% of asthma patients. Despite the increasing interest in ACO, there are still substantial controversies regarding its definition and its position within clinical guidelines for patients with obstructive lung disease. In general, most definitions indicate that ACO patients must present with non-reversible airflow limitation, significant exposure to smoking or other noxious particles or gases, together with features of asthma. In patients with a primary diagnosis of COPD, the identification of ACO has therapeutic implication because the asthmatic component should be treated with inhaled corticosteroids and some studies suggest that the most severe patients may respond to biological agents indicated for severe asthma. This manuscript aims to summarize the current state-of-the-art of ACO. The definitions, prevalence, and clinical manifestations will be reviewed and some innovative aspects, such as genetics, epigenetics, and biomarkers will be addressed. Lastly, the management and prognosis will be outlined as well as the position of ACO in the COPD and asthma guidelines.

A Real World Study to Assess the Effectiveness of Switching to Once Daily Closed Triple Therapy from Mono/Dual Combination or Open Triple Therapy in Patients with Chronic Obstructive Pulmonary Disease

Objective

This real world study evaluated the effectiveness of switching to closed triple therapy from mono/dual combination or open triple therapy in patients with chronic obstructive pulmonary disease (COPD).

Methods

We conducted this retrospective study at a single medical center from December 2014 to September 2020. Patients with COPD who were stepped up to triple therapy were enrolled. We analyzed the duration from initial COPD management to open or closed triple therapy and identified the clinical predictors of the patients who needed triple therapy early. We also evaluated the effectiveness of triple therapy after switching from initial management, and closed triple therapy after switching from open triple therapy.

Results

A total 115 COPD patients who were stepped up to triple therapy from initial treatment were analyzed. The duration from initial treatment to triple therapy was 22.4 months. The baseline peripheral blood eosinophil counts of the patients who switched to triple therapy early (n=63, less than 22 months) and those who switched to triple therapy later (n=52, more than 22 months) were similar (489.6 vs 434.5 cells/uL; p=0.589). After univariate and multivariate analysis, the patients who were older had more acute exacerbations (AEs) in the previous year, asthma and COPD overlap (ACO), and initial dual bronchodilator therapy were stepped up to triple therapy early. The FEV1 of the patients was significantly increased after switching to open triple therapy from mono bronchodilator therapy. In addition, switching from initial or open triple therapy to closed triple therapy significantly reduced the incidence of AEs.

Conclusion

COPD patients with high blood eosinophilia, older age, more AEs in the previous year, ACO, and initial dual bronchodilator therapy were stepped up to triple therapy early. Triple therapy showed improvements in lung function of most patients switching from mono bronchodilator therapy. After switching to closed triple therapy further reduced the incidence of AEs.

Recognizing and Seizing the Opportunities That Value-Based Payment Models Offer Behavioral Health Care

The rapid rise of value-based payment (VBP) models presents both new opportunities and challenges for behavioral health providers, especially in health systems that serve low-income and marginalized communities. This column discusses the experience of a community health care system as an early adopter of VBP in order to demonstrate both the constraints and possibilities health systems face when implementing VBP models. This example and the lessons drawn from it can assist other health systems seeking to implement these models.

A field guide to U.S. healthcare reform: The evolution to value-based healthcare

OBJECTIVE

A consolidated state-of-the-art review of U.S. healthcare reform efforts that documents the evolution towards value-based healthcare (VBH) is lacking in peer-review literature. This field guide attempts to clarify working definitions and conceptual boundaries within the lexicon of U.S. healthcare reform efforts that predated and have common thematic perspectives within the evolving VBH reform paradigm.

DATA SOURCES

Pubmed/MEDLINE/Google search.

REVIEW METHODS

Pubmed/MEDLINE/Google search was performed during August 1, 2020-January14, 2021 for U.S. healthcare reform terms, legislative and government agency publications. Those citing relevant legislative, regulatory, philosophical and technological advancements integral to the development and function of VBH were catalogued according to the targeted stakeholders and evolving reform strategy or technology.

CONCLUSIONS

Eight healthcare reform paradigms were identified as influential precursors to VBH: Patient-Centered Care Model, Patient-Centered Medical Home, Population Health, Personalized Medicine, P4 Medicine, Precision Medicine, Managed Care, and Accountable Care. Several of these models have similar nomenclature and, confusingly, many have multiple interpretations of the terms used to describe these models. However, consistent stakeholders identified within these paradigms are key to VBH; notably the patient, the physician and the payer (the "Big 3"). Demonstrable healthcare spending reductions have been best achieved when the Big 3 stakeholder interests are aligned within healthcare reform legislation. The definition of "Value" within each reform model was found to be based upon the perspective of the targeted stakeholder. Within VBH, the perspectives of the Big 3 stakeholders form a multidimensional meaning of "Value" that can be represented by the equation Value = Patient Experience Management 3 .