Radial force within two-stage axial-flow blood pump based on LES

Radial force in implantable two-stage axial flow blood pump (Artificial Heart) is a major factor affecting the operation stability. In order to investigate the transient operation characteristics of two-stage blood pumps, three-dimensional, unsteady numerical simulations were conducted by using the large eddy simulation (LES) model, PISO algorithm based on the sliding mesh technique in Fluent. The performance of the pump was obtained and compared with the experimental results. Besides, the radial force at various monitoring points were acquired; next, they were analyzed in time and frequency domains, respectively. It was demonstrated that the radial force at all the monitoring points changes periodically with time, its number of periods is identical to the number of blades but less affected by the number of guide vane blades, its frequency is close to the blade passing frequency. The frequency of radial force within the impeller increases gradually towards the impeller outlet and approaches the maximum value there, while the variation tendency of the frequency is opposite within the guide vane. The mostly dramatic radial force occurs at the impeller outlet, the main frequency at various monitoring points is almost equal to the impeller passing frequency. The amplitude of radial force coefficient at the monitoring points in the second stage impeller is higher than the first stage impeller. Additionally, the main frequency of radial force in the first stage impeller is different from the second stage guide vane

Disruption of Smad7 Promotes ANG II-Mediated Renal Inflammation and Fibrosis via Sp1-TGF-β/Smad3-NF.κB-Dependent Mechanisms in Mice

Smad7 is an inhibitory Smad and plays a protective role in obstructive and diabetic kidney disease. However, the role and mechanisms of Smad7 in hypertensive nephropathy remains unexplored. Thus, the aim of this study was to investigate the role and regulatory mechanisms of Smad7 in ANG II-induced hypertensive nephropathy. Smad7 gene knockout (KO) and wild-type (WT) mice received a subcutaneous infusion of ANG II or control saline for 4 weeks via osmotic mini-pumps. ANG II infusion produced equivalent hypertension in Smad7 KO and WT mice; however, Smad7 KO mice exhibited more severe renal functional injury as shown by increased proteinuria and reduced renal function (both p<0.05) when compared with Smad7 WT mice. Enhanced renal injury in Smad7 KO mice was associated with more progressive renal fibrosis with elevated TGF-β/Smad3 signalling. Smad7 KO mice also showed more profound renal inflammation including increased macrophage infiltration, enhanced IL-1β and TNF-α expression, and a marked activation of NF-κB signaling (all p<0.01). Further studies revealed that enhanced ANG II-mediated renal inflammation and fibrosis in Smad7 KO mice were also associated with up-regulation of Sp1 but downregulation of miR-29b expression. Taken together, the present study revealed that enhanced Sp1-TGF-β1/Smad3-NF-κB signaling and loss of miR-29 may be mechanisms by which deletion of Smad7 promotes ANG II-mediated renal fibrosis and inflammation. Thus, Smad7 may play a protective role in ANG II-induced hypertensive kidney disease. © 2013 Liu et al.published_or_final_versio

Siglec15 is a prognostic indicator and a potential tumor-related macrophage regulator that is involved in the suppressive immunomicroenvironment in gliomas

BackgroundSiglec15 is rising as a promising immunotherapeutic target in bladder, breast, gastric, and pancreatic cancers. The aim of the present study is to explore the prognostic value and immunotherapeutic possibilities of Siglec15 in gliomas using bioinformatics and clinicopathological methods.MethodsThe bioinformatics approach was used to examine Siglec15 mRNA expression in gliomas based on TCGA, CGGA, and GEO datasets. Then, the predictive value of Siglec15 expression on progression-free survival time (PFST) and overall survival time (OST) in glioma patients was comprehensively described.The TCGA database was screened for differentially expressed genes (DEGs) between the high and low Siglec15 expression groups, and enrichment analysis of the DEGs was performed. The Siglec15 protein expression and its prognostic impact in 92 glioma samples were explored using immunohistochemistry Next, the relationships between Siglec15 expression and infiltrating immune cells, immune regulators and multiple immune checkpoints were analysed.ResultsBioinformatics analyses showed that high Siglec15 levels predicted poor clinical prognosis and adverse recurrence time in glioma patients. In the immunohistochemical study serving as a validation set, Siglec15 protein overexpression was found in 33.3% (10/30) of WHO grade II, 56% (14/25) of WHO grade III, and 70.3% (26/37) of WHO grade IV gliomas respectively. Siglec15 protein overexpression was also found to be an independent prognostic indicator detrimental to the PFST and OST of glioma patients. Enrichment analysis showed that the DEGs were mainly involved in pathways associated with immune function, including leukocyte transendothelial migration, focal adhesion, ECM receptor interaction, and T-cell receptor signaling pathways. In addition, high Siglec15 expression was related to M2 tumor-associated macrophages (TAMs), N2 tumor-infiltrating neutrophils, suppressive tumor immune microenvironment, and multiple immune checkpoint molecules. Immunofluorescence analysis confirmed the colocalization of Siglec15 and CD163 on TAMs.ConclusionSiglec15 overexpression is common in gliomas and predicts an adverse recurrence time and overall survival time. Siglec15 is a potential target for immunotherapy and a potential TAMs regulator that is involved in the suppressed immunomicroenvironment in gliomas

Measurement-based correlation approach for power system dynamic response estimation

Understanding power system dynamics is essential for online stability assessment and control applications. Global positioning system-synchronised phasor measurement units and frequency disturbance recorders (FDRs) make power system dynamics visible and deliver an accurate picture of the overall operation condition to system operators. However, in the actual field implementations, some measurement data can be inaccessible for various reasons, for example, most notably failure of communication. In this study, a measurement-based approach is proposed to estimate the missing power system dynamics. Specifically, a correlation coefficient index is proposed to describe the correlation relationship between different measurements. Then, the auto-regressive with exogenous input identification model is employed to estimate the missing system dynamic response. The US Eastern Interconnection is utilised in this study as a case study. The robustness of the correlation approach is verified by a wide variety of case studies as well. Finally, the proposed correlation approach is applied to the real FDR data for power system dynamic response estimation. The results indicate that the correlation approach could help select better input locations and thus improve the response estimation accuracy

Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study

Introduction. Switchingfrom polluting (e.g. wood, crop waste, coal)to clean (e.g. gas, electricity) cooking fuels can reduce household air pollution exposures and climate-forcing emissions.While studies have evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role of different multilevel factors in household fuel switching, outside of interventions and across diverse community settings, is not well understood. Methods.We examined longitudinal survey data from 24 172 households in 177 rural communities across nine countries within the Prospective Urban and Rural Epidemiology study.We assessed household-level primary cooking fuel switching during a median of 10 years offollow up (∼2005–2015).We used hierarchical logistic regression models to examine the relative importance of household, community, sub-national and national-level factors contributing to primary fuel switching. Results. One-half of study households(12 369)reported changing their primary cookingfuels between baseline andfollow up surveys. Of these, 61% (7582) switchedfrom polluting (wood, dung, agricultural waste, charcoal, coal, kerosene)to clean (gas, electricity)fuels, 26% (3109)switched between different polluting fuels, 10% (1164)switched from clean to polluting fuels and 3% (522)switched between different clean fuels

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation