Aging is a significant risk factor for many neurodegenerative diseases and neurological tumors. Previous studies indicate that the frailty index, facial aging, telomere length (TL), and epigenetic ...aging clock acceleration are commonly used biological aging proxy indicators. This study aims to comprehensively explore potential relationships between biological aging and neurodegenerative diseases and neurological tumors by integrating various biological aging proxy indicators, employing Mendelian randomization (MR) analysis.
Two-sample bidirectional MR analyses were conducted using genome-wide association study (GWAS) data. Summary statistics for various neurodegenerative diseases and neurological tumors, along with biological aging proxy indicators, were obtained from extensive meta-analyses of GWAS. Genetic single-nucleotide polymorphisms (SNPs) associated with the exposures were used as instrumental variables, assessing causal relationships between three neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis), two benign neurological tumors (vestibular schwannoma and meningioma), one malignant neurological tumor (glioma), and four biological aging indicators (frailty index, facial aging, TL, and epigenetic aging clock acceleration). Sensitivity analyses were also performed.
Our analysis revealed that genetically predicted longer TL reduces the risk of Alzheimer's disease but increases the risk of vestibular schwannoma and glioma (All Glioma, GBM, non-GBM). In addition, there is a suggestive causal relationship between some diseases (PD and GBM) and DNA methylation GrimAge acceleration. Causal relationships between biological aging proxy indicators and other neurodegenerative diseases and neurological tumors were not observed.
Building upon prior investigations into the causal relationships between telomeres and neurodegenerative diseases and neurological tumors, our study validates these findings using larger GWAS data and demonstrates, for the first time, that Parkinson's disease and GBM may promote epigenetic age acceleration. Our research provides new insights and evidence into the causal relationships between biological aging and the risk of neurodegenerative diseases and neurological tumors.
Myocardial infarction (MI) is an acute and persistent myocardial ischemia caused by coronary artery disease. This study screened potential genes related to MI. Three gene expression datasets related ...to MI were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened using the MetaDE package. Afterward, the modules and genes closely related to MI were screened and a gene co-expression network was constructed. A support vector machine (SVM) classification model was then constructed based on the GSE61145 dataset using the e1071 package in R. A total of 98 DEGs were identified in the MI samples. Next, three modules associated with MI were screened and an SVM classification model involving seven genes was constructed. Among them,
BCL6, CEACAM8
, and
CUGBP2
showed co-interactions in the gene co-expression network. Therefore,
ACOX1, BCL6, CEACAM8,
and
CUGBP2
, in addition to
GPX7
, might be feature genes related to MI.
The charging operation is rapidly becoming a key concern for highway charging station operation as the electric vehicle charging demand for highway traveling rises. This paper proposes a charging ...price-setting scheme for highway charging station operation, considering distributed renewable energy generators neighboring highway charging stations. For this purpose, a bi-level approach is proposed in this paper to model the conflicting objectives between the highway charging station operator and electric vehicles to optimize charging price and their routes. The upper level is designed to optimize the highway charging station operation's profit. The lower level characterizes the charging behavior of EVs via a time-space network model. To solve the proposed bi-level model, we adopt the column-and-constraint generation algorithm to obtain an optimal result. The performance of the proposed scheme is illustrated by numerical case studies based on an experimental highway system.
The present work aims to fabricate CrMnFeCoNi high-entropy alloy (HEA) possessing outstanding wear and corrosion properties via laser additive manufacturing (LAM) and subsequent laser shock peening ...(LSP). The surface morphology, microstructure, microhardness and residual stress of LAM-fabricated specimen were characterized before and after LSP. Additionally, sliding wear and electrochemical corrosion experiments were conducted to evaluate the suitability of LSP for improving wear and corrosion resistance. Results indicated that friction coefficients and wear rates of LAM-fabricated specimens obviously decreased after LSP. Both untreated and LSP-treated specimens displayed uniform wear mechanisms, including abrasive and adhesive wear, while the wear damage level of the high-energy LSP-treated specimen was the mildest. Moreover, LSP-treated specimens exhibited lower corrosion current density and higher corrosion potential as compared with the untreated specimen, suggesting an enhancement in corrosion resistance. The hardened surface layer had positive effects on inhibiting furrow and spalling to resist material removal, and the compressive residual stress enhanced the adhesion of tribo-layers on the worn surface to protect the underlying layer from further damage. The grain refinement and compressive residual stress synergistically contributed to form compact passive films, thereby restraining the aggression of corrosive ions to enhance the corrosion resistance.
•LAM-fabricated CrMnFeCoNi HEA is treated by LSP.•LSP improves the wear and corrosion resistance of LAM-fabricated CrMnFeCoNi HEA.•The wear and corrosion mechanisms of CrMnFeCoNi HEA treated by LSP are discussed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this work, we proposed a surface modification strategy to improve corrosion resistance of magnesium alloy by combining laser surface texturing (LST) with phosphate conversion coating (PCC). The ...surface and section morphologies, adhesive performance and electrochemical corrosion properties of the coated samples were investigated. Results demonstrate that the multimodal surface roughness and high specific area generated by LST facilitate the deposition of coating, increase the adhesion of coating and reduce the shedding rate of coating in the scratch test. Electrochemical analyses reveal that the coated sample with LST pretreatment shows superior corrosion properties, and fewer areas were damaged by corrosive medium compared with the coated sample without LST. Immersion test results reveal that LTC sample shows the best long-term corrosion resistance among all samples.The underlying mechanisms of the PCC with LST pretreatment to improve the anticorrosive performance of Mg alloys are proposed.
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•Multimodal surface roughness and high specific area generated by LST facilitate the deposition of PCC.•LST pretreatment reduce the defects and increase the adhesion of PCC.•The PCCs with the LST pretreatment exhibit excellent corrosion resistance.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The autonomous mobility-on-demand (AMoD) system provides an alternative solution for sustainable and economical transportation system. Meanwhile, battery swapping could become a promising approach to ...sustain the efficient operation of EV fleet. This article proposes a combined operation scheme for battery swapping station (BSS) and AMoD system. To maximizing the profit of AMoD system, an expanded network flow model is employed to determine swapping scheduling and vehicle rebalancing for EV fleet in AMoD system. The interaction between the shared mobility-on-demand system and BSS is modeled by the swapping demand and swapping price. Specifically, swapping demand is determined in the AMoD system and introduced as known parameters in the BSS problem. Fleet management operation in AMoD system will be influenced by swapping price provided by BSS. The BSS management problem is formulated as a mixed-integer linear programming model, which optimizes refueling decisions for depleted batteries. Simulation experiments based on real-world data from New York City are provided. The results demonstrate the effectiveness of this proposed integrated operation model.
Considering its unique operational characteristics, the autonomous mobility-on-demand (AMoD) system is playing a more and more critical role in the future transportation system. In this article, we ...consider a joint planning problem of autonomous fleet (i.e., vehicle type and fleet size) and charging infrastructure (i.e., the size of charging piles with various charging rates, distributed renewable resources) while accounting for the spatial-temporal demand-side flexibility of the AMoD system. We adopt an augmented network flow model to capture the autonomous fleet's charging, order serving, and rebalancing decisions. The proposed planning problem is modeled as a two-stage stochastic program and solved by multicut Benders decomposition techniques. Simulation experiments based on real-world data are performed to demonstrate the effectiveness of the proposed planning scheme.
A procedure for the prediction of talc content in wheat flour based on radial basis function (RBF) neural network and near-infrared spectroscopy (NIRS) data is described. In this study, 41 wheat ...flour samples adulterated with different concentrations of talc were used. The diffuse reflectance spectra of all samples were collected by NIRS analyzer in the spectral range of 400 to 2,500 nm. A sample of outliers was eliminated by Mahalanobis distance based on near-infrared spectral scanning, and the remaining 40 wheat flour samples were used for spectral characteristic analysis. A calibration set of 26 samples and a prediction set of 14 samples of wheat flour were built as a result of sample set partitioning based on joint
-
distances division. A comparison of Savitzky-Golay smoothing, multiplicative scatter correction (MSC), first derivation, second derivation, and standard normal variation in the modeling showed that MSC has the best preprocessing effect. To develop a simpler, more efficient prediction model, the correlation coefficient method (CCM) was used to reduce spectral redundancy and determine the maximum correlation informative wavelength (MIW). From the full 1,050 wavelengths, 59 individual MIWs were finally selected. The optimal combined detection model was CCM-MSC-RBF based on the selected MIWs, with a determination of prediction coefficients of prediction (
p) of 0.9999, root-mean-square error of prediction of 0.0765, and residual predictive deviation of 65.0909. The study serves as a proof of concept that NIRS technology combined with multivariate analysis has the potential to provide a fast, nondestructive and reliable assay for the prediction of talc content in wheat flour.
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CEKLJ, GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
