Cardiovascular disease risk models and dementia or cognitive decline: a systematic review

BackgroundHealth cognitive promotion and protection is a critical topic. With the world’s aging population and rising life expectancy, there will be many people living with highly age-related dementia illnesses. Cardiovascular disease (CVD) and dementia share the same risk factors, such as unhealthy lifestyles and metabolic factors. These recognized risks associated with CVD and dementia frequently co-occur. CVD risk models may have a close association with dementia and cognitive decline. So, this systematic review aimed to determine whether CVD risk models were connected with dementia or cognitive decline and compare the predictive ability of various models.MethodsPubMed, Web of Science, PsychINFO, Embase, Cochrane Library, CNKI, Sinomed, and WanFang were searched from 1 January 2014 until 16 February 2023. Only CVD risk models were included. We used the Newcastle-Ottawa scale (NOS) for the quality assessment of included cohort studies and the Agency for Healthcare Research and Quality (AHRQ) for cross-sectional studies. The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement’s guidelines were followed in this systematic study.ResultsIn all, 9,718 references were screened, of which 22 articles were included. A total of 15 CVD risk models were summarized. Except for the Cardiovascular Health in Ambulatory Care Research Team (CANHEART) health index, the other 14 CVD risk models were associated with dementia and cognitive decline. In comparison, different CVD risk models and domain-specific cognitive function correlation variation depended on cohort characteristics, risk models, cognitive function tests, and study designs. Moreover, it needed to be clarified when comparing the predicting performance of different CVD risk models.ConclusionIt is significant for public health to improve disease risk prediction and prevention and mitigate the potential adverse effects of the heart on the brain. More cohort studies are warranted to prove the correlation between CVD risk models and cognitive function. Moreover, further studies are encouraged to compare the efficacy of CVD risk models in predicting cognitive disorders

Cross-Layer Design of Automotive Systems

With growing system complexity and closer cyber-physical interaction, there are increasingly stronger dependencies between different function and architecture layers in automotive systems. This paper first introduces several cross-layer approaches we developed in the past for holistically addressing multiple system layers in the design of individual vehicles and of connected vehicle applications; and then presents a new methodology based on the weakly-hard paradigm for leveraging the scheduling flexibility in architecture layer to improve the system performance at function layer. The results of these works demonstrate the importance and effectiveness of cross-layer design for automotive systems

Superpixel-Based Weighted Sparse Regression and Spectral Similarity Constrained for Hyperspectral Unmixing

With the support of spectral libraries, sparse unmixing techniques have gradually developed. However, some existing sparse unmixing algorithms suffer from problems, such as insufficient utilization of spatial information and sensitivity to noise. To solve these problems, this article proposes a novel hyperspectral unmixing algorithm, called superpixel-based weighted sparse regression and spectral similarity constrained unmixing. In the proposed method, a precalculated weight is introduced to help enhance sparsity of abundances, which is obtained from coarse abundance estimation. It also maintains spatial consistency in a local region of a hyperspectral image to mitigate the negative influence of noise. Additionally, the method selects optimal neighborhood pixels in the local region by combining spatial and spectral information and constructs a similarity matrix to explore spectral similarity in the subspace. Meanwhile, superpixel segmentation is considered as an auxiliary method to obtain local regions in the unmixing process. Experiments performed on synthetic and real data demonstrate that the proposed method achieves more accurate abundance estimation than other comparison algorithms

Transcriptomic Profiling of Human Placental Trophoblasts in Response to Infection with Enterococcus faecalis

Increasing evidence suggests that Enterococcus faecalis strains can pass through placental barriers and cause adverse outcomes during pregnancy. However, the underlying molecular mechanism of the interaction between E. faecalis and the host placental barrier has yet to be fully elucidated. In this study, we have used DNA microarray analysis to investigate the response of human placental trophoblast-like BeWo cells to infection with E. faecalis OG1RF. These results indicate that a total of 2191 genes in BeWo cells are differentially expressed in the presence of E. faecalis OG1RF, with 1357 genes being upregulated and 834 genes being downregulated. These differentially expressed genes (DEGs) are involved in apoptosis, stress and stimulus response, placental and embryonic development, immune response, and cell adhesion. Therefore, these results provide information on the molecular mechanisms that E. faecalis invasion can trigger to cause adverse pregnancy outcomes

How to Choose In Vitro Systems to Predict In Vivo Drug Clearance: A System Pharmacology Perspective

The use of in vitro metabolism data to predict human clearance has become more significant in the current prediction of large scale drug clearance for all the drugs. The relevant information (in vitro metabolism data and in vivo human clearance values) of thirty-five drugs that satisfied the entry criteria of probe drugs was collated from the literature. Then the performance of different in vitro systems including Escherichia coli system, yeast system, lymphoblastoid system and baculovirus system is compared after in vitro-in vivo extrapolation. Baculovirus system, which can provide most of the data, has almost equal accuracy as the other systems in predicting clearance. And in most cases, baculovirus system has the smaller CV in scaling factors. Therefore, the baculovirus system can be recognized as the suitable system for the large scale drug clearance prediction

MOFs-derived core-shell Co3Fe7@Fe2N nanopaticles supported on rGO as high-performance bifunctional electrocatalyst for oxygen reduction and oxygen evolution reactions

© 2020 Elsevier Ltd Exploring stable and highly efficient bifunctional electrocatalysts for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is critical for the novel energy conversion and storage devices including fuel cells and metal-air batteries. Herein, the core-shell structured Co3Fe7@Fe2N nanoparticles supported on reduced graphene oxide (rGO) nanosheets (Co3Fe7@Fe2N/rGO) is designed though the simple annealing of MOFs. The as-fabricated samples present an excellent electrocatalytic performance for ORR and OER due to the synergistic effect of electrode materials. The Co3Fe7@Fe2N/rGO exhibits an onset potential of 0.98 V (vs. Reversible hydrogen electrode), peak current intensity of 1.531 A g−1 and long-term stability for ORR, which is close to that of the benchmark Pt/C (20%) in 0.1 M KOH. It also shows good oxygen evolution reaction (OER) performance with an overpotential of 371 mV (at 10 mA cm−2). When used as a bifunctional air electrode in Zn-air batteries, the core-shell materials enabled an excellent mass power density of 60 W cm−2 g−1 at 0.57 V and stable cycling performance for over 100 cycles

Soybean milk derived carbon intercalated with reduced graphene oxide as high efficient electrocatalysts for oxygen reduction reaction

Exploring high-performance and low-cost metal-free oxygen reduction reaction (ORR) catalysts from biomass-derived materials is vital to the development of novel energy conversion devices such as fuel cells, etc. Herein, nitrogen-enriched soybean milk derived carbon (BDC/rGO-HT-NH3) intercalated with reduced graphene oxide (rGO) electrocatalyst is prepared via one-pot hydrothermal synthesis method followed with nitridation by NH3. The resultant catalyst with high surface area, good conductivity and high content of N (9.4 at.%) shows high electrocatalytic activity towards ORR in alkaline medium, which mainly happens through the direct 4-electron pathway. The onset potential of BDC/rGO-HT-NH3 catalyzed ORR is 0.96 V vs RHE, which is only 0.11 V lower than that of the commercial Pt/C (20 wt%) catalyst. In addition, the BDC/rGO-HT-NH3 catalyst shows superior long-term running durability. The desirable catalytic performances enable the facile synthesis approach of BDC/rGO-HT-NH3 to be a promising methodology for transforming other biomass materials to N-enriched carbon based materials as low-cost and environmental friendly catalysts for ORR. (C)2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved