Numerical Study on the Elastic Deformation and the Stress Field of Brittle Rocks under Harmonic Dynamic Load

Funding: The support of National Natural Science Foundation of China (No. 51704074) and Youth Science Foundation of Heilongjiang Province (No. QC2018049) are gratefully acknowledged. The work is also supported by Talent Cultivation Foundation (No. SCXHB201703; No. ts26180119; No. td26180141) and Youth Science Foundation (No. 2019QNL-07) of Northeast Petroleum University.Peer reviewedPublisher PD

酵母におけるオルガネラ間ステロール輸送機構に関する研究

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 堀内 裕之, 東京大学教授 佐藤 隆一郎, 東京大学准教授 足立 博之, 東京大学准教授 有岡 学, 東京大学准教授 舘川 宏之University of Tokyo(東京大学

Factoring Electrochemical and Full-Lifecycle Aging Modes of Battery Participating in Energy and Transportation Systems

Transportation electrification emerges as a pivotal strategy to realize deep decarbonization for many countries, and the central part of this is battery. However, a key challenge often overlooked is the impact of battery aging on the economy and longevity of electric vehicles (EVs). To address this issue, the paper proposes a novel battery full-life degradation (FLD) model and energy management framework that substantially improves the overall economic efficiency of Battery Energy Storage Systems (BESS). In the first stage, battery electrochemical aging features are modeled by learning cell fading rate under various healthy states, capitalized on the Stanford experimental open dataset. Accordingly, a lifecycle degradation model is then developed considering various operational conditions and aging stages to quantitatively assess the effects of depth of discharge, C-rate, state of health, and state of charge. In the second stage, battery electrochemical aging features are integrated into vehicle energy management so that batteries under different fading rates can be flexibly utilized during whole lifecycles. The proposed methods are validated on a practical UK distribution network and a hybrid vehicles hardware-in-the-loop platform. With the proposed methods, EV users can make informed decisions to optimize energy usage and prolong the lifespan of vehicle BESS, thereby fostering a more sustainable and efficient transportation infrastructure.</p

MFAP3L activation promotes colorectal cancer cell invasion and metastasis

AbstractAn abundance of microfibril-associated glycoprotein 3-like (MFAP3L) significantly correlates with distant metastasis in colorectal cancer (CRC), although the mechanism has yet to be explained. In this study, we observed that MFAP3L knock-down resulted in reduced CRC cell invasion and hepatic metastasis. We evaluated the cellular location and biochemical functions of MFAP3L and found that this protein was primarily localized in the nucleus of CRC cells and acted as a protein kinase. When EGFR translocated into the nucleus upon stimulation with EGF, MFAP3L was phosphorylated at Tyr287 within its SH2 motif, and the activated form of MFAP3L phosphorylated ERK2 at Thr185 and Tyr187. Moreover, the metastatic behavior of CRC cells in vitro and in vivo could be partially explained by activation of the nuclear ERK pathway through MFAP3L phosphorylation. Hence, we experimentally demonstrated for the first time that MFAP3L likely participates in the nuclear signaling of EGFR and ERK2 and acts as a novel nuclear kinase that impacts CRC metastasis

Factoring Electrochemical and Full-Lifecycle Aging Modes of Battery Participating in Energy and Transportation Systems

Transportation electrification emerges as a pivotal strategy to realize deep decarbonization for many countries, and the central part of this is battery. However, a key challenge often overlooked is the impact of battery aging on the economy and longevity of electric vehicles (EVs). To address this issue, the paper proposes a novel battery full-life degradation (FLD) model and energy management framework that substantially improves the overall economic efficiency of Battery Energy Storage Systems (BESS). In the first stage, battery electrochemical aging features are modeled by learning cell fading rate under various healthy states, capitalized on the Stanford experimental open dataset. Accordingly, a lifecycle degradation model is then developed considering various operational conditions and aging stages to quantitatively assess the effects of depth of discharge, C-rate, state of health, and state of charge. In the second stage, battery electrochemical aging features are integrated into vehicle energy management so that batteries under different fading rates can be flexibly utilized during whole lifecycles. The proposed methods are validated on a practical UK distribution network and a hybrid vehicles hardware-in-the-loop platform. With the proposed methods, EV users can make informed decisions to optimize energy usage and prolong the lifespan of vehicle BESS, thereby fostering a more sustainable and efficient transportation infrastructure.</p

Genetic association of the gut microbiota with epigenetic clocks mediated by inflammatory cytokines: a Mendelian randomization analysis

BackgroundA new aging biomarker epigenetic clock has been developed. There exists a close link between aging and gut microbiota, which may be mediated by inflammatory cytokines. However, the relationship between the epigenetic clock, gut microbiota, and the mediating substances is unclear.MethodsTwo large genome-wide association meta-analyses were analyzed by two-sample Mendelian randomization. The results between gut microbiota and epigenetic clock were investigated using the four methods (Inverse variance weighted, MR-Egger, weighted median, MR-PRESSO). Genetic correlation was measured by Linked disequilibrium score regression (LDSC). The correctness of the study direction was checked by the Steiger test. Cochran’s Q statistic and MR-Egger intercept were used as sensitivity analyses of the study. The two-step method was used to examine the mediating role of inflammatory cytokines. We use the Benjamini-Hochberg correction method to correct the P value.ResultsAfter FDR correction, multiple bacterial genera were significantly or suggestively associated with four epigenetic clocks (GrimAge, HannumAge, IEAA, PhenoAge). And we detected several inflammatory factors acting as mediators of gut microbiota and epigenetic clocks.ConclusionThis study provides genetic evidence for a positive and negative link between gut microbiota and aging risk. We hope that by elucidating the genetic relationship and potential mechanisms between aging and gut microbiota, we will provide new avenues for continuing aging-related research and treatment

Causal association of circulating cholesterol levels with dementia: a mendelian randomization meta-analysis

Prospective studies have shown that abnormally circulating cholesterol is associated with the risk of dementia. However, whether the association is causal or not remains unclear. We attempt to infer the causal association in a MR meta-analysis by using ApoE gene polymorphisms as instrument variables. Studies with dementia risk (27 studies) or circulating lipid levels (7 studies) were included, with totally 3136 dementia patients and 3103 healthy controls. The analyses showed that carriers of ε2 allele significantly were of decreased risk of AD (OR = 0.70; 95% CI: 0.58–0.84; P \u3c 0.01), whereas carriers of ε4 allele were of increased risk of AD (OR = 3.62; 95% CI: 3.03–4.32; P \u3c 0.05), compared to these of ε3 allele. Circulating TC was significantly reduced in carriers of ε2 allele (WMD = − 0.29 mmol/L; 95% CI: −0.54 to −0.03; P \u3c 0.05) and increased in carriers of ε4 allele (WMD = 0.42 mmol/l; 95% CI: 0.001–0.84; P \u3c 0.05). In addition, carriers of ε4 allele had reduction in circulating HDL-C (WMD = − 0.04 mmol/L; 95% CI: − 0.07 to −0.001; P \u3c 0.05). In comparing allele ε2 with ε3, the predicted OR of having AD for 1 mg/dL increment in circulating TC was 0.97 (95% CI: 0.86–0.98; P \u3c 0.05). Comparing allele ε4 with ε3, the predicted OR for a 1 mg/dL increment in TC was 1.08 (95% CI: 1.05–17.58; P \u3c 0.05), and reduction in HDL-C was 2.30 (95% CI: 1.51–43.99; P \u3c 0.05). Our findings demonstrate that high circulating TC and reduced HDL-C levels might be potential risk factors of the development of AD

Isolation and characterization of Stenotrophomonas pavanii GXUN74707 with efficient flocculation performance and application in wastewater treatment

The identification of microorganisms with excellent flocculants-producing capability and optimization of the fermentation process are necessary for the wide-scale application of bioflocculants. Therefore, we isolated and identified a highly efficient flocculation performance strain of Stenotrophomonas pavanii GXUN74707 from the sludge. The optimal fermentation and flocculation conditions of strain S. pavanii GXUN74707 was in fermentation medium with glucose and urea as the carbon and nitrogen sources, respectively, at pH 7.0 for 36 h, which treatment of kaolin suspension with 0.5 mL of the fermentation broth resulted in a flocculation rate of 99.0%. The bioflocculant synthesized by strain S. pavanii GXUN74707 was found mainly in the supernatant of the fermentation broth. Chemical analysis revealed that the pure bioflocculant consisted of 79.70% carbohydrates and 14.38% proteins. The monosaccharide components of MBF-GXUN74707 are mainly mannose (5.96 μg/mg), galactose (1.86 μg/mg), and glucose (1.73 μg/mg). Infrared spectrometric analysis showed the presence of carboxyl (COO-), hydroxyl (-OH) groups. The SEM images showed clumps of rod-shaped bacteria with adhesion of extracellular products. Furthermore, the strain decolored dye wastewater containing direct black, direct blue, and Congo red by 89.2%, 95.1%, 94.1%, respectively. The chemical oxygen demand (COD) and biological oxygen demand (BOD) removal rates after treatment of aquaculture wastewater with the fermentation broth were 68% and 23%, respectively. This study is the first to report the performance and application of strain Stenotrophomonas pavanii in wastewater flocculation. The results indicate that strain S. pavanii is a good candidate for the production novel bioflocculants and demonstrates its potential industrial practicality in biotechnology processes

Spatial-temporal diffusion model of aggregated infectious diseases based on population life characteristics: a case study of COVID-19

Outbreaks of infectious diseases pose significant threats to human life, and countries around the world need to implement more precise prevention and control measures to contain the spread of viruses. In this study, we propose a spatial-temporal diffusion model of infectious diseases under a discrete grid, based on the time series prediction of infectious diseases, to model the diffusion process of viruses in population. This model uses the estimated outbreak origin as the center of transmission, employing a tree-like structure of daily human travel to generalize the process of viral spread within the population. By incorporating diverse data, it simulates the congregation of people, thus quantifying the flow weights between grids for population movement. The model is validated with some Chinese cities with COVID-19 outbreaks, and the results show that the outbreak point estimation method could better estimate the virus transmission center of the epidemic. The estimated location of the outbreak point in Xi'an was only 0.965 km different from the actual one, and the results were more satisfactory. The spatiotemporal diffusion model for infectious diseases simulates daily newly infected areas, which effectively cover the actual patient infection zones on the same day. During the mid-stage of viral transmission, the coverage rate can increase to over 90%, compared to related research, this method has improved simulation accuracy by approximately 18%. This study can provide technical support for epidemic prevention and control, and assist decision-makers in developing more scientific and efficient epidemic prevention and control policies