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Abstract Objective The objective of this study was to investigate the potential association between the inflammatory burden index (IBI) and the prevalence of chronic inflammatory airway diseases (CIAD), as well as mortality rates among individuals diagnosed with CIAD. Methods Participants were sourced from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2010. The IBI was calculated using the formula: IBI = C-reactive protein * neutrophils / lymphocytes. CIAD comprised self-reported asthma, chronic bronchitis, and chronic obstructive pulmonary disease (COPD). Mortality outcomes, including all-cause and respiratory disease mortality, were determined through linked data from the National Death Index (NDI) up to December 2019. Results A total of 27,495 adults were included. IBI was divided into quartiles, with the lowest quartile as the reference group. After adjusting for confounding variables, a positive correlation was observed between higher IBI and increased prevalence of total CIAD (OR = 1.383 [1.215–1.575]), asthma (OR = 1.267 [1.096–1.465]), chronic bronchitis (OR = 1.568 [1.263–1.946]), and COPD (OR = 1.907 [1.311–2.774]). Over a median follow-up of 12.33 [9.92-16.00] years, there were 1221 deaths from all causes and 220 deaths from respiratory disease among 4499 patients with CIAD. Following multivariate adjustments, the fourth quartile was significantly associated with increased risk of all-cause mortality (HR = 2.227 [1.714–2.893]) and respiratory disease mortality (HR = 2.748 [1.383–5.459]) compared to the first quartile of IBI in CIAD participants. Moreover, variable importance analysis using a random survival forest model demonstrated the significance of IBI in predicting mortality from both all-cause and respiratory diseases. Conclusion IBI exhibited an association with the prevalence of CIAD, with higher IBI levels correlating with elevated all-cause and respiratory disease mortality among individuals with CIAD.

Objective: The objective of this study was to investigate the potential association between the inflammatory burden index (IBI) and the prevalence of chronic inflammatory airway diseases (CIAD), as well as mortality rates among individuals diagnosed with CIAD. Methods: Participants were sourced from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2010. The IBI was calculated using the formula: IBI = C-reactive protein * neutrophils / lymphocytes. CIAD comprised self-reported asthma, chronic bronchitis, and chronic obstructive pulmonary disease (COPD). Mortality outcomes, including all-cause and respiratory disease mortality, were determined through linked data from the National Death Index (NDI) up to December 2019. Results: A total of 27,495 adults were included. IBI was divided into quartiles, with the lowest quartile as the reference group. After adjusting for confounding variables, a positive correlation was observed between higher IBI and increased prevalence of total CIAD (OR = 1.383 [1.215–1.575]), asthma (OR = 1.267 [1.096–1.465]), chronic bronchitis (OR = 1.568 [1.263–1.946]), and COPD (OR = 1.907 [1.311–2.774]). Over a median follow-up of 12.33 [9.92-16.00] years, there were 1221 deaths from all causes and 220 deaths from respiratory disease among 4499 patients with CIAD. Following multivariate adjustments, the fourth quartile was significantly associated with increased risk of all-cause mortality (HR = 2.227 [1.714–2.893]) and respiratory disease mortality (HR = 2.748 [1.383–5.459]) compared to the first quartile of IBI in CIAD participants. Moreover, variable importance analysis using a random survival forest model demonstrated the significance of IBI in predicting mortality from both all-cause and respiratory diseases. Conclusion: IBI exhibited an association with the prevalence of CIAD, with higher IBI levels correlating with elevated all-cause and respiratory disease mortality among individuals with CIAD. [ABSTRACT FROM AUTHOR]

ObjectiveThe objective of this study was to investigate the potential association between dietary fiber intakes and the prevalence of chronic inflammatory airway diseases (CIAD), as well as mortality in participants with CIAD.MethodsData was collected from the National Health and Nutrition Examination Survey (NHANES) 2013–2018, with dietary fiber intakes being calculated as the average of two 24-h dietary reviews and divided into four groups. CIAD included self-reported asthma, chronic bronchitis, and chronic obstructive pulmonary disease (COPD). Through December 31, 2019, mortality was identified from the National Death Index. In cross-sectional studies, multiple logistic regressions were used to assess dietary fiber intakes associated with the prevalence of total and specific CIAD. Dose–response relationships were tested using restricted cubic spline regression. In prospective cohort studies, cumulative survival rates were calculated using the Kaplan–Meier method and compared using log-rank tests. Multiple COX regressions were used to assess dietary fiber intakes associated with mortality in participants with CIAD.ResultsA total of 12,276 adults were included in this analysis. The participants had a mean age of 50.70 ± 17.4 years and was 47.2% male. The prevalence of CIAD, asthma, chronic bronchitis, and COPD were 20.1, 15.2, 6.3, and 4.2%, respectively. The median daily consumption of dietary fiber was 15.1 [IQR 10.5, 21.1] g. After adjusting for all confounding factors, linear and negative associations were observed between dietary fiber intakes and the prevalence of total CIAD (OR = 0.68 [0.58–0.80]), asthma (OR = 0.71 [0.60–0.85]), chronic bronchitis (OR = 0.57 [0.43–0.74]) and COPD (OR = 0.51 [0.34–0.74]). In addition, the fourth quartile of dietary fiber intake levels remained significantly associated with a decreased risk of all-cause mortality (HR = 0.47 [0.26–0.83]) compared to the first quartile.ConclusionDietary fiber intakes were found to be correlated with the prevalence of CIAD, and higher dietary fiber intakes were associated with a reduced mortality in participants with CIAD.

Congenital isolated adrenocorticotropic hormone deficiency (CIAD) is a rare disorder that may be conducive to hypoglycemia, cholestasis, and seizures. We reported on two siblings with a homozygous mutation of the TBX19 gene, C.377 (exon2) C>T, p. P126L. Their parents had heterozygous mutations on the same locus. Glucocorticoid supplementary therapy was effective, but the treatment became delayed due to inaccessibility, which resulted in entirely different clinical outcomes for the siblings. The older brother developed subdural hematoma, intractable epilepsy, and developmental delays. In contrast, the younger sister received timely glucocorticoid replacement therapy and had no long-term complications while maintaining a good quality of life. In summary, when CIAD is confirmed, early intervention is essential to achieve the optimal outcome.

Abstract Global demand for oil and gas is still increasing rapidly. The direct consequence of this is the increased operating pressure amid concerns over increasing sand production. According to the Society of Petroleum Engineers (SPE), 70% of the world's hydrocarbon reserves are contained in reservoirs situated on unconsolidated formations. Given the reality of these formations, sand production will certainly be a problem of significant concern particularly during the later life of the fields when they become more 'mature'. However, to monitor sand and optimise its production for improved recovery and safety, life extension and economy of the fields and ensured reliability, the automatic detection and prediction of sand flow characteristic measurements; sand flow rate (SFR), sand concentration (SC), line pressure drop (PD), and gas velocity (GV), has become an important research topic of great interest. Despite this importance, discussion of the topic is still lacking in the literature. This paper proposes a novel and robust architecture of intelligent real-time sand flow characteristic measurement using an acoustic sensor and computational intelligence assisted design (CIAD) framework. It fully incorporates acoustic signal processing and analysis, prediction algorithms and optimisation algorithms in the design. Acoustic features based on acoustic signal processing techniques are extracted to reduce the dimensionality of the acoustic signals. A classical Artificial Neural Network (ANN) is used to model the non-linear relationships between the acoustic signal characteristics and the flow characteristics measurands. In addition, the ANN algorithm adapts its weights and biases using the Grey Wolf Optimiser (GWO) through minimisation of the cost function during the training phase. Preliminary results obtained on a laboratory test rig demonstrate that an acoustic sensor coupled with CIAD may provide simple and robust practical solution to the measurement problem of particle-laden gas flow characteristics in real-time. Highlights • Architecture of intelligent real-time sand flow characteristic measurement. • Real-time quantitative monitoring of detection and prediction the concentration of sand in gas pipeline. • Optimal design using computational intelligence assisted design framework. • ANN adapts weights and biases using the grey wolf optimiser through minimisation of the cost function. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to investigate the potential association between dietary fiber intakes and the prevalence of chronic inflammatory airway diseases (CIAD), as well as mortality in participants with CIAD., Methods: Data was collected from the National Health and Nutrition Examination Survey (NHANES) 2013-2018, with dietary fiber intakes being calculated as the average of two 24-h dietary reviews and divided into four groups. CIAD included self-reported asthma, chronic bronchitis, and chronic obstructive pulmonary disease (COPD). Through December 31, 2019, mortality was identified from the National Death Index. In cross-sectional studies, multiple logistic regressions were used to assess dietary fiber intakes associated with the prevalence of total and specific CIAD. Dose-response relationships were tested using restricted cubic spline regression. In prospective cohort studies, cumulative survival rates were calculated using the Kaplan-Meier method and compared using log-rank tests. Multiple COX regressions were used to assess dietary fiber intakes associated with mortality in participants with CIAD., Results: A total of 12,276 adults were included in this analysis. The participants had a mean age of 50.70 ± 17.4 years and was 47.2% male. The prevalence of CIAD, asthma, chronic bronchitis, and COPD were 20.1, 15.2, 6.3, and 4.2%, respectively. The median daily consumption of dietary fiber was 15.1 [IQR 10.5, 21.1] g. After adjusting for all confounding factors, linear and negative associations were observed between dietary fiber intakes and the prevalence of total CIAD (OR = 0.68 [0.58-0.80]), asthma (OR = 0.71 [0.60-0.85]), chronic bronchitis (OR = 0.57 [0.43-0.74]) and COPD (OR = 0.51 [0.34-0.74]). In addition, the fourth quartile of dietary fiber intake levels remained significantly associated with a decreased risk of all-cause mortality (HR = 0.47 [0.26-0.83]) compared to the first quartile., Conclusion: Dietary fiber intakes were found to be correlated with the prevalence of CIAD, and higher dietary fiber intakes were associated with a reduced mortality in participants with CIAD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Lin, Zhu and Zhang.)

Polymer electrolyte fuel cells (PEFCs) have attracted considerable interest within the research community due to the increasing demands for renewable energy. Within the PEFCs’ many components, a cathode electrode plays a primary function in the operation of the cell. Here, a computational-intelligence-aided design and engineering (CIAD/CIAE) framework with potential cross-disciplinary applications is proposed to minimize the over-potential difference η and improve the overall efficiency of PEFCs. A newly developed swarm dolphin algorithm is embedded in a computational-intelligence-integrated solver to optimize a triple-layer cathode electrode model. The simulation results demonstrate the potential application of the proposed CIAD/CIAE framework in the design automation and optimization of PEFCs. [ABSTRACT FROM AUTHOR]

Abstract: High electricity consumption is of concern to the world for a variety of reasons, including its social-economic-environmental coupled impacts on well-being of individuals, social life and the federal energy policies. This paper proposes a quantitative model to examine the long-term relationship between annual electricity consumption and its major macroeconomic variables, including gross domestic product, electricity price, efficiency, economic structure, and carbon dioxide emission, using computational intelligence aided design (CIAD). It develops a firefly algorithm with variable population (FAVP) to obtain the parameters of the electricity consumption model through optimising two proposed trend indices: moving mean of the average precision (mmAP) and moving mean of standard derivation (mmSTD). The model is validated with empirical electricity consumption data in China between 1980 and 2012, based on which the error of approximations between 1980 and 2009 is ±15% and the error of predictions between 2010 and 2012 is [−8%, −5%]. The main contributions of this research are to develop: (1) a novel quantitative model that can accurately predict the social, economic and environmental coupled impacts on the annual electricity demands; (2) the conceptual CIAD framework; (3) FAVP algorithm; and (4) two new trend indices of mmAP and mmSTD. The findings of this research can assist the decision makers in resolving the conflict between energy consumption growth and carbon emission reduction without dooming the economic prosperity in the long run. [Copyright &y& Elsevier]