Micro-analysis of hanging sleeper dynamic interactions with ballast bed

The hanging sleeper under train dynamic loads result in discrete contact and breakage of ballast particles, and accelerate ballast bed degradation and deformation. A sleeper-ballast dynamic interaction model was established to analyze the effects of hanging sleeper due to the sleeper dynamic response. In this research, the Discrete Element Method (DEM) was applied to simulate the hanging sleeper dynamic characteristics of ballast bed, where the irregular ballast particle was constructed by clusters, and the ballast particle breakage under dynamic cyclic loads was investigated. The nonlinear contact force model of Mohr-Coulomb was adopted to model the cluster particles. The ballast breakage function and dynamic simulation were employed, with local damping method. Numerical results indicated that hanging sleeper altered the contact force distribution state, the hanging sleepers would incur centralized contact force under sleepers, more ballast particles breakage, and ballast lateral resistance reduction varied with hanging sleeper situations. Some ballasted track improvements should be considered in practice, such as increase thickness of ballast bed, improve ballast compaction, and reduce vibration tamping produced voids

Coenzyme Q deficiency may predispose to sudden unexplained death via an increased risk of cardiac arrhythmia

Cardiac arrhythmia is currently considered to be the direct cause of death in a majority of sudden unexplained death (SUD) cases, yet the genetic predisposition and corresponding endophenotypes contributing to SUD remain incompletely understood. In this study, we aimed to investigate the involvement of Coenzyme Q (CoQ) deficiency in SUD. First, we re-analyzed the exome sequencing data of 45 SUD and 151 sudden infant death syndrome (SIDS) cases from our previous studies, focusing on previously overlooked genetic variants in 44 human CoQ deficiency-related genes. A considerable proportion of the SUD (38%) and SIDS (37%) cases were found to harbor rare variants with likely functional effects. Subsequent burden testing, including all rare exonic and untranslated region variants identified in our case cohorts, further confirmed the existence of significant genetic burden. Based on the genetic findings, the influence of CoQ deficiency on electrophysiological and morphological properties was further examined in a mouse model. A significantly prolonged PR interval and an increased occurrence of atrioventricular block were observed in the 4-nitrobenzoate induced CoQ deficiency mouse group, suggesting that CoQ deficiency may predispose individuals to sudden death through an increased risk of cardiac arrhythmia. Overall, our findings suggest that CoQ deficiency-related genes should also be considered in the molecular autopsy of SUD

Protein Co-Enrichment Analysis of Extracellular Vesicles

Extracellular Vesicles (EVs) carry cell-derived proteins that confer functionality and selective cell uptake. However, whether proteins are packaged stochastically or co-enriched within individual EVs, and whether co-enrichment fluctuates under homeostasis and disease, has not been measured. EV abundance and protein global relative expression have been qualified by bulk analysis. Meanwhile, co-enrichment is not directly accessible via bulk measurement and has not been reported for single EV analysis. Here, we introduce the normalized index of co-enrichment (NICE) to measure protein co-enrichment. NICE was derived by (i) capturing EVs based on the expression of a membrane-bound protein, (ii) probing for the co-expression of a second protein at the population level - EV integrity underwrites the detection of single EV co-expression without the need to resolve single EVs - and (iii) normalizing measured values using two universal normalization probes. Axiomatically, NICE = 1 for stochastic inclusion or no overall co-enrichment, while for positive and negative co-enrichment NICE > 1 or < 1, respectively. We quantified the NICE of tetraspanins, growth factor receptors and integrins in EVs of eight breast cancer cell lines of varying metastatic potential and organotropism, combinatorially mapping up to 104 protein pairs. Our analysis revealed protein enrichment and co-expression patterns consistent with previous findings. For the organotropic cell lines, most protein pairs were co-enriched on EVs, with the majority of NICE values between 0.2 to 11.5, and extending from 0.037 to 80.4. Median NICE were either negative, neutral or positive depending on the cells. NICE analysis is easily multiplexed and is compatible with microarrays, bead-based and single EV assays. Additional studies are needed to deepen our understanding of the potential and significance of NICE for research and clinical uses

A promoting role of androgen receptor in androgen-sensitive and -insensitive prostate cancer cells

Although the vital role of the androgen receptor (AR) has been well demonstrated in primary prostate cancers, its role in the androgen-insensitive prostate cancers still remains unclear. Here, we used a small hairpin RNA approach to directly assess AR activity in prostate cancer cells. Reduction of AR expression in the two androgen-sensitive prostate cancer cell lines, LNCaP and LAPC4, significantly decreased AR-mediated transcription and cell growth. Intriguingly, in two androgen-insensitive prostate cell lines, LNCaP-C42B4 and CWR22Rv1, knockdown of AR expression showed a more pronounced effect on AR-induced transcription and cell growth than androgen depletion. Using cDNA microarrays, we also compared the transcriptional profiles induced by either androgen depletion or AR knockdown. Although a significant number of transcripts appear to be regulated by both androgen depletion and AR knockdown, we observed a subset of transcripts affected only by androgen depletion but not by AR knockdown, and vice versa. Finally, we demonstrated a direct role for AR in promoting tumor formation and growth in a xenograft model. Taken together, our results elucidate an important role for the AR in androgen-insensitive prostate cancer cells, and suggest that AR can be used as a therapeutic target for androgen-insensitive prostate cancers

Development of a CT image analysis-based scoring system to differentiate gastric schwannomas from gastrointestinal stromal tumors

PurposeTo develop a point-based scoring system (PSS) based on contrast-enhanced computed tomography (CT) qualitative and quantitative features to differentiate gastric schwannomas (GSs) from gastrointestinal stromal tumors (GISTs).MethodsThis retrospective study included 51 consecutive GS patients and 147 GIST patients. Clinical and CT features of the tumors were collected and compared. Univariate and multivariate logistic regression analyses using the stepwise forward method were used to determine the risk factors for GSs and create a PSS. Area under the receiver operating characteristic curve (AUC) analysis was performed to evaluate the diagnostic efficiency of PSS.ResultsThe CT attenuation value of tumors in venous phase images, tumor-to-spleen ratio in venous phase images, tumor location, growth pattern, and tumor surface ulceration were identified as predictors for GSs and were assigned scores based on the PSS. Within the PSS, GS prediction probability ranged from 0.60% to 100% and increased as the total risk scores increased. The AUC of PSS in differentiating GSs from GISTs was 0.915 (95% CI: 0.874–0.957) with a total cutoff score of 3.0, accuracy of 0.848, sensitivity of 0.843, and specificity of 0.850.ConclusionsThe PSS of both qualitative and quantitative CT features can provide an easy tool for radiologists to successfully differentiate GS from GIST prior to surgery

Characterizing Carbon Emissions and the Associations with Socio-Economic Development in Chinese Cities

Reducing carbon emissions in cities is crucial for addressing climate change, while the city-level emissions of different compositions and their relationships with socio-economic features remain largely unknown in China. Here, we explored the city-level emission pattern from the industrial, transportation, and household sectors and the emission intensity, as well as their associations with socio-economic features in China, using the up-to-date (2020) CO2 emissions based on 0.1&deg; grid (10 &times; 10 km) emission data. The results show that: (1) CO2 emissions from the industrial sector were considerably dominant (78%), followed by indirect (10%), transportation (8%), and household (2%) emissions on the national scale; (2) combining total emissions with emission intensity, high emission&ndash;high intensity cities, which are the most noteworthy regions, were concentrated in the North, while low emission&ndash;low intensity types mainly occurred in the South-West; (3) cities with a higher GDP tend to emit more CO2, while higher-income cities tend to emit less CO2, especially from the household sector. Cities with a developed economy, as indicated by GDP and income, would have low emissions per GDP, representing a high emission efficiency. Reducing the proportion of the secondary sector of the economy could significantly decrease CO2 emissions, especially for industrial cities. Therefore, the carbon reduction policy in China should focus on the industrial cities in the North with high emission&ndash;high intensity performance. Increasing the income and proportion of the tertiary industry and encouraging compact cities can effectively reduce the total emissions during the economic development and urbanization process

Stressing State Analysis of SRC Column with Modeling Test and Finite Element Model Data

This paper reveals the failure characteristic points of the spiral reinforced column during the damage process by modeling and analyzing the stressing state of the column with the test and finite element output data. At the same time, the structural stressing state theory and the correlation modeling analysis method’s applicability to spiral reinforced concrete columns are verified. First, a finite element model was established based on the literature’s spiral reinforced concrete column tests. Then, correlation modeling was performed on the test strain data to obtain correlation characteristic pairs (mode-characteristic parameters), and stressing state modeling was performed on the internal energy and element strain energy data from the finite element model to obtain stressing state characteristic pairs. The slope increment criterion is applied to the obtained stressing state characteristic parameter curves to reveal the characteristic point Q, defined as the failure starting point. The reasonableness of the failure starting point is further verified by observing the cloud diagram of the finite element model in the vicinity of the characteristic point Q. In general, the correlation modeling method proposed in this paper can provide a new reference for structural stressing state analysis. In addition, the failure starting point of spiral reinforced concrete columns revealed in this paper can be used as a design reference

Research on the General Failure Law of a CTRC Column by Modeling FEM Output Data

In this paper, a finite element model (FEM) is developed based on a set of circular steel tube reinforced concrete (CTRC) columns with axial compression and eccentric compression tests. The stressing state characteristics of the FEM are modeled in the form of characteristic pairs (mode-characteristic parameters) based on the structural stressing state theory and the proposed correlation modeling method. The slope increasing criterion is applied to the correlation characteristic parameter curve to obtain the characteristic point Q where the CTRC stressing state undergoes a qualitative change, and the characteristic point Q is defined as the new failure load point of the CTRC column. By selecting the element strain energy density at different locations of the FEM for correlation stressing state modeling and dividing the correlation stressing state sub-modes (concrete, steel tube, vertical reinforcement, and stirrup reinforcement), the structural stressing state theory and the rationality of the proposed correlation stressing state modeling method are verified. In addition, the certainty and reasonableness of the failure load points of the CTRC columns are revealed and verified

Stressing State Analysis of SRC Column with Modeling Test and Finite Element Model Data

This paper reveals the failure characteristic points of the spiral reinforced column during the damage process by modeling and analyzing the stressing state of the column with the test and finite element output data. At the same time, the structural stressing state theory and the correlation modeling analysis method&rsquo;s applicability to spiral reinforced concrete columns are verified. First, a finite element model was established based on the literature&rsquo;s spiral reinforced concrete column tests. Then, correlation modeling was performed on the test strain data to obtain correlation characteristic pairs (mode-characteristic parameters), and stressing state modeling was performed on the internal energy and element strain energy data from the finite element model to obtain stressing state characteristic pairs. The slope increment criterion is applied to the obtained stressing state characteristic parameter curves to reveal the characteristic point Q, defined as the failure starting point. The reasonableness of the failure starting point is further verified by observing the cloud diagram of the finite element model in the vicinity of the characteristic point Q. In general, the correlation modeling method proposed in this paper can provide a new reference for structural stressing state analysis. In addition, the failure starting point of spiral reinforced concrete columns revealed in this paper can be used as a design reference

Stressing state features of H-steel columns under cyclic biaxial bending action revealed from experimental residual strains

In this paper, the stressing state modeling analysis of the residual strain data of H-steel columns reveals three characteristic points that exist during the failure of H-steel columns. Also, the correctness of the stressing state analysis method, residual, and buckling characteristic pairs was verified. First, the experimental residual strains were transformed into generalized strain energy density (GSED) values as the state variables for establishing the stressing state mode and characteristic parameters (characteristic pairs). The Mann-Kendall (M-K) criterion is applied to the normalized GSED sum-j curves to reveal the characteristic points P, Q, and U of the evolving stressing state of the H-steel column. Characteristic point P is defined as the elastic-plastic branch point of the H-steel column, characteristic point Q is defined as the failure starting point, and characteristic point U is defined as the progressive failure point. Around the characteristic points of the H-steel columns, the directly modeled stressing state characteristic pairs, residual characteristic pairs, and buckling characteristic pairs produce significant mutation characteristics. This phenomenon verifies the correctness of the revealed H-steel column characteristic points and the rationality of this paper's stressing state modeling method. Then, it is proposed that the elastic-plastic branch point P can be directly used as the design reference point, and it is compared with the design point given by Code EN1993–1–5. In conclusion, this paper provides new ideas for analyzing steel structures and opens up the value of residual strain data in structural analysis