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Abstract Trace element levels in the circulation (blood, serum, plasma) are believed to play a role in the pathophysiologic processes of Alzheimer’s disease (AD); however, there is heterogeneity in the available findings. This study conducted a systematic review and meta-analysis of trace elements (including: copper (Cu), iron (Fe), zinc (Zn), selenium (Se), lead (Pb), cadmium (Cd), mercury (Hg), manganese (Mn), aluminum (Al), arsenic (As), and magnesium (Mg)) in AD patients and controls to assess the variation of trace elements in the circulation of AD patients. By systematically screening case–control studies on circulatory trace element levels in AD patients from 2000 to the present in the PubMed, Web of Science, and MEDLINE databases, 52 studies were included in the final meta-analysis. The results of the random-effects model showed significantly elevated circulatory levels of Cd (SMD = 0.79, 95% CI: 0.35, 1.24), Hg (SMD = 0.59, 95% CI: 0.03, 1.16), and Cu (SMD = 0.70, 95% CI: 0.37, 1.04) in AD patients, while levels of Fe (SMD = − 0.58, 95% CI: − 1.03, − 0.13), Se (SMD = − 0.53, 95% CI: − 0.85, − 0.21), and Zn (SMD = − 0.99, 95% CI: − 1.52, − 0.46) were significantly lower. The database formed in this study provides reliable population-based research evidence for exploring changes in circulating trace element levels in AD patients. Monitoring and stabilization of circulatory trace element levels in the elderly may be a potential preventive target for AD.

With the incredible growth of the scale and complexity of datasets, creating proper visualizations for users becomes more and more challenging in large datasets. Though several visualization recommendation systems have been proposed, so far, the lack of practical engineering inputs is still a major concern regarding the usage of visualization recommendations in the industry. In this paper, we proposed AVA, an open-sourced web-based framework for Automated Visual Analytics. AVA contains both empiric-driven and insight-driven visualization recommendation methods to meet the demands of creating aesthetic visualizations and understanding expressible insights respectively. The code is available at https://github.com/antvis/AVA.

Background: Oral health is of fundamental importance to maintain systemic health in humans. Stem cell-based oral tissue regeneration is a promising strategy to achieve the recovery of impaired oral tissue. As a highly conserved process of lysosomal degradation, autophagy induction regulates stem cell function physiologically and pathologically. Autophagy activation can serve as a cytoprotective mechanism in stressful environments, while insufficient or over-activation may also lead to cell function dysregulation and cell death. Aim of review: This review focuses on the effects of autophagy on stem cell function and oral tissue regeneration, with particular emphasis on diverse roles of autophagy in different oral tissues, including periodontal tissue, bone tissue, dentin pulp tissue, oral mucosa, salivary gland, maxillofacial muscle, temporomandibular joint, etc. Additionally, this review introduces the molecular mechanisms involved in autophagy during the regeneration of different parts of oral tissue, and how autophagy can be regulated by small molecule drugs, biomaterials, exosomes/RNAs or other specific treatments. Finally, this review discusses new perspectives for autophagy manipulation and oral tissue regeneration. Key scientific concepts of review: Overall, this review emphasizes the contribution of autophagy to oral tissue regeneration and highlights the possible approaches for regulating autophagy to promote the regeneration of human oral tissue.

Due to the diversity of postpartum depression (PPD) patients and the complexity of associated pathophysiological changes, most current animal models cannot accurately simulate PPD-like symptoms. In this study, we established a reliable animal model for PPD by inducing chronic unpredictable mild stress (CUMS) at different stages (pre-pregnancy, pregnancy, or postnatal) in female mice, followed by maternal separation (MS) from day 2–21 after delivery. The results for female mice subjected to pre-pregnancy stress were not statistically significant due to a lower conception rate. However, female mice exposed to CUMS during either the gestational or postnatal stage, followed by MS, successfully exhibited PPD-like symptoms. The models were deemed effective based on observed behavioral abnormalities, impaired hippocampal neuron functioning, and reduced serum concentrations of neurotransmitters (5-HT, GABA, and NE). Additionally, mice that underwent gestational CUMS followed by MS displayed a more dysfunctional hypothalamic-pituitary-adrenal (HPA) axis and more severe uterine inflammation. The study also investigated the impact of PPD on the behavior and neurodevelopment of adolescent offspring through behavioral tests, enzyme-linked immunosorbent assay (ELISA), hematoxylin-eosin (HE) staining, and western blotting (WB). The results indicated that adolescent offspring of mothers with PPD exhibited behavioral and neurodevelopmental disorders, with male offspring being more susceptible than females. Female mice exposed to both CUMS and MS during the postnatal period had more severe adverse effects on their offspring compared to the other model groups.

Abstract Reservoirs exert a profound influence on the cycling of dissolved organic matter (DOM) in inland waters by altering flow regimes. Biological incubations can help to disentangle the role that microbial processing plays in the DOM cycling within reservoirs. However, the complex DOM composition poses a great challenge to the analysis of such data. Here we tested if the interpretable machine learning (ML) methodologies can contribute to capturing the relationships between molecular reactivity and composition. We developed time‐specific ML models based on 7‐day and 30‐day incubations to simulate the biogeochemical processes in the Three Gorges Reservoir over shorter and longer water retention periods, respectively. Results showed that the extended water retention time likely allows the successive microbial degradation of molecules, with stochasticity exerting a non‐negligible effect on the molecular composition at the initial stage of the incubation. This study highlights the potential of ML in enhancing our interpretation of DOM dynamics over time.

Abstract Aims/Introduction Serum amyloid A (SAA) is an acute phase reactive protein that plays a vital role in the early diagnosis, risk prediction, efficacy observation and prognosis evaluation of infectious diseases. This study aimed to assess the association between SAA levels and the prognosis of patients with coronavirus disease 2019 (COVID‐19) and diabetes. Materials and Methods We carried out this retrospective cohort study from March 2022 to May 2022. The population was stratified by tertiles of SAA levels: low (36 mg/L). The primary outcome was whether the patient developed severe COVID‐19, and secondary outcomes included the need for invasive mechanical ventilation and length of hospital stay. Logistic regression analyses were carried out to identify risk factors affecting the prognosis of patients with COVID‐19 and diabetes. Results We analyzed 910 diabetes patients with COVID‐19. The median age of the patients was 69 years, and 52.3% were men. As SAA levels increased, the proportion of severe COVID‐19 (6.3% vs 7.3% vs 22.8%, P 36 mg/L further increased the odds ratio to 4.423 (P 36 mg/L remained an independent risk factor for the development of severe COVID‐19 (adjusted odds ratio 3.038, P

In order to study the adsorption characteristics of gas and oxygen in coal seams containing ferrous disulfide, the molecular structure model of anthracite and the structural model of ferrous disulfide were constructed respectively, and the adsorption isotherms of ferrous disulfide crystal and anthracite for single component O2 and CH4 were calculated. Based on the experimental data of inorganic sulfur content in coal, the structural models of ferrous disulfide and anthracite were mixed in different proportions, and the structural models of anthracite with inorganic sulfur content of 1.17 %, 2.61 %, 0.75 % and 3.78 % were established, and the adsorption characteristics of O2 and CH4 were calculated and analyzed. The results show that the adsorption rate of single component O2 in FeS2 is higher than that of CH4, which is greatly influenced by pressure and temperature. The binding capacity of O2 with S is stronger than that with Fe, and CH4 is diagonally adsorbed in ferrous disulfide crystal. At 0 ∼ 1 MPa, the adsorption capacity of anthracite for CH4 is greater than that of O2; After 1 MPa, the adsorption rate and capacity of O2 were higher than that of CH4. With the increase of FeS2 content doped with anthracite, the adsorption capacity of CH4 and O2 decreased. When binary components O2 and CH4 are adsorbed on FeS2-doped anthracite, the larger the proportion of O2, the closer the sum of adsorption capacity of mixed gas is to that of single component gas.

IntroductionEmotional words are often used as stimulus material to explore the cognitive and emotional characteristics of individuals with depressive disorder, while normal individuals mostly rate the scores of affective words. Given that individuals with depressive disorder exhibit a negative cognitive bias, it is possible that their depressive state could influence the ratings of affective words. To enhance the validity of the stimulus material, we specifically recruited patients with depression to provide these ratings.MethodsThis study provided subjective ratings for 501 Chinese affective norms, incorporating 167 negative words selected from depressive disorder patients’ Sino Weibo blogs, and 167 neutral words and 167 positive words selected from the Chinese Affective Word System. The norms are based on the assessments made by 91 patients with depressive disorder and 92 normal individuals, by using the paper-and-pencil quiz on a 9-point scale.ResultsRegardless of the group, the results show high reliability and validity. We identified group differences in three dimensions: valence, arousal, and self-relevance: the depression group rated negative words higher, but positive and neutral words lower than the normal control group.ConclusionThe emotional perception affected the individual’s perception of words, to some extent, this database expanded the ratings and provided a reference for exploring norms for individuals with different emotional states.

Summary: To maintain an effective barrier, intestinal progenitor cells must divide at a rate that matches the loss of dead and dying cells. Otherwise, epithelial breaches expose the host to systemic infection by gut-resident microbes. Unlike most pathogens, Vibrio cholerae blocks tissue repair by arresting progenitor proliferation in the Drosophila model. At present, we do not understand how V. cholerae circumvents such a critical antibacterial defense. We find that V. cholerae blocks epithelial repair by activating the growth inhibitor bone morphogenetic protein (BMP) pathway in progenitors. Specifically, we show that interactions between V. cholerae and gut commensals initiate BMP signaling via host innate immune defenses. Notably, we find that V. cholerae also activates BMP and arrests proliferation in zebrafish intestines, indicating an evolutionarily conserved link between infection and failure in tissue repair. Our study highlights how enteric pathogens engage host immune and growth regulatory pathways to disrupt intestinal epithelial repair.

IntroductionCloud fitness is transforming indoor exercise for young people in China. Recent studies have explored the correlation between media use and health-promoting behavior by examining the motivation of individuals and the credibility of influencers. However, the role of media affordance has thus far been largely overlooked. Drawing on the theory of Stimulus-Organism-Response (SOR), the study investigated the indirect effect of visibility affordance on the intention to exercise with fitness influencers in the context of cloud fitness through psychological variables.MethodsThis paper, based on the online survey data (N = 456), analyses the effect of visibility affordance on the intention to fitness following with influencers. A moderated parallel mediation model was constructed to examine the relationship among related variables.ResultsThe paper draws the following conclusions: (1) Visibility affordance is positively related to the intention to exercise with fitness influencers. (2) Both the sense of social presence and immersion positively mediate the relationship between visibility affordance and the intention to exercise with fitness influencers. (3) The perceived popularity of the influencer positively moderates the relationship between social presence and the intention to exercise with fitness influencers and moderates the mediating role of social presence.DiscussionConsequently, this study enhances the existing body of knowledge in exercise behavior and health communication literature, and provides practical implications for short video platform, influencers and individuals in promoting healthier behaviors.

In order to solve the problem of strength and toughness of aluminum matrix composites, TiO2/Al matrix composites were prepared by friction stir processing(FSP). The experiments were carried out by microstructure observation test, tensile test and micro-hardness test to characterize and analyze the strengthening mechanism, microstructure and mechanical properties of composites. The results show that with the introduction of TiO2, the grain has been refined, and the crystalline form of Al is change from continuous dynamic recrystallization(CDRX) of invisible core to the particle-stimulated nucleation mechanism by FSP. The tensile strength and microhardness of the composite are improved. When the addition amount reaches 48%（mass fraction）, the tensile strength is 456 MPa, and the hardness is 130 HV, which increases by 17% and 16%, respectively, compared with that of the unadded particles, and the elongation decreases only by 4%. TiO2 prepared by FSP can effectively improve the mechanical properties and improve the strength and toughness mismatch, which provides theoretical basis and technical reference for the application of new composite materials.

Summary: Vibrio cholerae is an aquatic bacterium that causes severe and potentially deadly diarrheal disease. Despite the impact on global health, our understanding of host mucosal responses to Vibrio remains limited, highlighting a knowledge gap critical for the development of effective prevention and treatment strategies. Using a natural infection model, we combine physiological and single-cell transcriptomic studies to characterize conventionally reared adult zebrafish guts and guts challenged with Vibrio. We demonstrate that Vibrio causes a mild mucosal immune response characterized by T cell activation and enhanced antigen capture; Vibrio suppresses host interferon signaling; and ectopic activation of interferon alters the course of infection. We show that the adult zebrafish gut shares similarities with mammalian counterparts, including the presence of Best4+ cells, tuft cells, and a population of basal cycling cells. These findings provide important insights into host-pathogen interactions and emphasize the utility of zebrafish as a natural model of Vibrio infection.

ABSTRACT About a quarter of the world’s population is infected with Mycobacterium tuberculosis, equivalent to about two billion people. With the emergence of multidrug-resistant tuberculosis, those existing anti-tuberculosis drugs no longer meet the demand for cure anymore; there is an urgent need for the development of new anti-tuberculosis drugs. Decaprenylphosphoryl-β-D-ribose 2´-epimerase (DprE1) has been proven to be a potential antimycobacterial target, and several inhibitors have entered clinical trial. Herein, we designed and synthesized a series of compounds based on the indole and benzomorpholine by using the strategy of scaffold hopping. The preferred compound B18 showed strong antimycobacterial activity in H37Rv and drug-resistant clinical isolates. In addition, compound B18 did not exhibit antimycobacterial efficacy against other species of strains. Subsequently, the target of B18 was identified as DprE1 by analyzing spontaneous compound-resistant mutation data, and a docking study was performed to illustrate the binding mode between B18 and DprE1. In general, compound B18 is compatible to current DprE1 inhibitors, even higher phosphodiesterase 6C selectivity and plasma protein binding rate, which represent a new type of effective reversible DprE1 inhibitor. IMPORTANCE Drug therapy remains the cornerstone of tuberculosis (TB) treatment, yet first-line anti-tuberculosis drugs are associated with significant adverse effects that can compromise patient outcomes. Moreover, prolonged and widespread use has led to an alarming rise in drug-resistant strains of Mycobacterium tuberculosis, including multidrug-resistant [MDR-tuberculosis (TB)] and extensively drug-resistant (XDR-TB) forms. Urgent action is needed to develop novel anti-tuberculosis agents capable of overcoming these challenges. We report that compound B18, a decaprenylphosphoryl-β-D-ribose 2´-epimerase inhibitor with a benzomorpholine backbone, exhibits potent activity against not only the non-pathogenic strain H37Ra, but also the pathogenic strain H37Rv and clinical MDR and XDR strains. Preliminary druggability studies indicate that B18 possesses high safety and acceptable pharmacokinetic properties, rendering it a promising candidate for further development as a novel anti-tuberculosis agent.

In pursuit of discovering novel anticancer agents, we designed and synthesized a series of novel 1,2,3-triazole hybrids based on cabotegravir analogues. These compounds were subjected to initial biological evaluations to assess their anticancer activities against non-small-cell lung cancer (NSCLC). Our findings indicated that some of these compounds exhibited promising antitumor abilities against H460 cells, while demonstrated less efficacy against H1299 cells. Notably, compound 5i emerged as the most potent, displaying an IC50 value of 6.06 μM. Furthermore, our investigations into cell apoptosis and reactive oxygen species (ROS) production revealed that compound 5i significantly induced apoptosis and triggered ROS generation. Additionally, Western blot analysis revealed the pronounced elevation of LC3 expression in H460 cells and γ-H2AX expression in H1299 cells subsequent to treatment with compound 5i. These molecular responses potentially contribute to the observed cell death phenomenon. These findings highlight the potential of compound 5i as a promising candidate for further development as an anticancer agent especially lung cancer.

Abstract Renal fibrosis is a common characteristic of various chronic kidney diseases (CKDs) driving the loss of renal function. During this pathological process, persistent injury to renal tubular epithelial cells and activation of fibroblasts chiefly determine the extent of renal fibrosis. In this study, the role of tumor protein 53 regulating kinase (TP53RK) in the pathogenesis of renal fibrosis and its underlying mechanisms is investigated. TP53RK is upregulated in fibrotic human and animal kidneys with a positive correlation to kidney dysfunction and fibrotic markers. Interestingly, specific deletion of TP53RK either in renal tubule or in fibroblasts in mice can mitigate renal fibrosis in CKD models. Mechanistic investigations reveal that TP53RK phosphorylates baculoviral IAP repeat containing 5 (Birc5) and facilitates its nuclear translocation; enhanced Birc5 displays a profibrotic effect possibly via activating PI3K/Akt and MAPK pathways. Moreover, pharmacologically inhibiting TP53RK and Birc5 using fusidic acid (an FDA‐approved antibiotic) and YM‐155(currently in clinical phase 2 trials) respectively both ameliorate kidney fibrosis. These findings demonstrate that activated TP53RK/Birc5 signaling in renal tubular cells and fibroblasts alters cellular phenotypes and drives CKD progression. A genetic or pharmacological blockade of this axis serves as a potential strategy for treating CKDs.

The timely identification of rail internal defects and the application of corresponding preventive measures would greatly reduce catastrophic failures, such as rail breakage. Ultrasonic rail defect detection is the current mainstream rail defect detection method thanks to its advantages of strong penetration, high accuracy, and ease to deploy. The 2D B-scan image output by ultrasonic detectors contains rich features of defects; however, rail engineers manually identify and localize the defect image, which can be time-consuming, and the image may be subject to missing identification or mistakes. This paper adopted state-of-the-art deep learning algorithms for novel B-scan images for the automatic identification and localization of rail internal tracks. First, through image pre-processing of classification, denoising, and augmentation, four categories of defect image datasets were established, namely crescent-shaped fatigue cracks, fishbolt hole cracks, rail web cracks, and rail base transverse cracks; then, four representatives of deep learning object detection networks, YOLOv8, YOLOv5, DETR, and Faster R-CNN, were trained with the defects dataset and further applied to the testing dataset for defect identification; finally, the performances of the three detection networks were compared and evaluated at the data level, the network structure level, and the interference adaptability level, respectively. The results show that the YOLOv8 network can effectively classify and localize four categories of internal rail defects in B-scan images with a 93.3% mean average precision at three images per second, and the detection time is 58.9%, 376.8%, and 123.2% faster than YOLO v5, DETR, and Faster R-CNN, respectively. The proposed approach could ensure the real-time, accurate, and efficient detection and analysis of internal defects to a rail.

Objective: Microgravity contributes to ocular injury yet the underlying mechanism remains unclear. This study aims to elucidate the mechanism behind choroidal circulation disorder and outer retinal degeneration in rats with simulated weightlessness.Methods: Optical coherence tomography angiography (OCTA) was used to evaluate choroidal circulation and retinal morphological alterations in rats with weightlessness simulation. Electroretinogram and transmission electron microscopy were used to examine the ultrastructure and function of the choroid and outer retina. Furthermore, histological and terminal deoxynucleotidyl transferase deoxyuridine dUTP nick-end labeling (TUNEL) staining was used to monitor retinal morphology. Western blotting was performed to analyze the expressions of blood-retinal outer barrier function-related proteins (Cx43, ZO-1, and occludin).Results: The choroidal thickening was observed from the fourth week of simulated weightlessness (p < 0.05), and choroidal capillary density started to decline by the fifth week (p < 0.05). Transmission electron microscopy revealed that the choroidal vessels were open and operating well by the fourth week. However, most of the mitochondria within the vascular endothelium underwent mild swelling, and by the fifth week, the choroidal vessels had various degrees of erythrocyte aggregation, mitochondrial swelling, and apoptosis. Additionally, ERG demonstrated a decline in retinal function beginning in the fifth week (p < 0.05). TUNEL staining revealed a significantly higher apoptotic index in the outer nuclear layer of the retina (p < 0.05). At the sixth week weeks of simulated weightlessness, OCTA and hematoxylin and eosin (HE) staining of retinal sections revealed that the outer nuclear layer of the retina started to become thin (p < 0.05). Results from western blotting revealed that Cx43, ZO-1, and occludin exhibited decreased expression (p < 0.05).Conclusion: Based on our findings in a rat model of simulated weightlessness, choroidal circulation disturbance induced by choroidal congestion is the initial cause of outer retinal degeneration. Blood-retinal barrier disruption is significant in this process.

Cangzhou is located in the northeast part of the North China Plain; here, groundwater is the main water source for production and living. Due to the serious regional land subsidence caused by long-term overexploitation of groundwater, the monitoring of land subsidence in this area is significant. In this paper, we used the Small Baseline Subsets Interferometric Point Target Analysis (SBAS-IPTA) technique to process the Envisat-ASAR, Radarsat-2, and Sentinel-1A data and obtained the land subsidence of Cangzhou from 2004 to 2020. Additionally, we obtained winter wheat distribution information in Cangzhou using the Pixel Information Expert Engine (PIE-Engine) remote sensing cloud platform. On this basis, we analyzed the relationship between ground water level, winter wheat planting area, and the response of land subsidence according to the land use type and groundwater level monitoring data near the winter wheat growing area. The results show that during 2004–2020, the average annual subsidence rate of many places in Cangzhou was higher than 30 mm/year, and the maximum subsidence rate was 115 mm/year in 2012. From 2004 to 2020, the area of the subsidence funnel showed a trend of first increasing and then decreasing. In 2020, the subsidence funnel area reached 6.9 × 103 km2. The winter wheat planting area in the urban area showed a trend of first decreasing, then increasing and then decreasing, and it accounted for a large proportion in the funnel area. At the same time, we studied the relationship between the land subsidence rate and the water level at different burial depths and the response of winter wheat planting area. The results showed that the change of confined water level had a stronger response with the other two variables.

Log-based public key infrastructure(PKI) refers to a robust class of CA-attack-resilient PKI that enhance transparency and accountability in the certificate revocation and issuance process by compelling certificate authorities (CAs) to submit revocations to publicly and verifiably accessible logs. However, log-based PKIs suffer from a reliance on centralized and consistent sources of information, rendering them susceptible to split-world attacks, and they regrettably fail to provide adequate incentives for recording or monitoring CA behavior. Blockchain-based PKIs address these limitations by enabling decentralized log audits through automated financial incentives. However, they continue to face challenges in developing a scalable revocation mechanism suited for lightweight clients. In this paper, we introduce BRT, a scalable blockchain-based system for certificate and revocation transparency. It serves to log, audit, and validate the status of certificates within the transport layer security (TLS)/secure sockets layer(SSL) PKI domain. We designed an audit-on-chain framework, coupled with an off-chain storage/computation system, to enhance the efficiency of BRT when operating in a blockchain environment. By implementing a blockchain-based prototype, we demonstrate that BRT achieves storage-efficient log recording with a peak compression rate reaching 8%, cost-effective log updates for large-scale certificates, and near-instantaneous revocation checks for users.

High-speed railways in the Beijing–Tianjin–Hebei (BTH) Plain are gradually becoming more widespread, covering a greater area. The operational safety of high-speed railways is influenced by the continuous development of land subsidence. It is necessary to predict the subsidence along the high-speed railways; thus, this work is of critical importance to the safety of high-speed railway operation. In this study, we processed Sentinel-1A data using the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique to acquire the land subsidence in the typical BTH area. Then, we combined the Empirical Mode Decomposition (EMD) and Gradient Boosting Decision Tree (GBDT) methods (EMD-GBDT) to forecast land subsidence along high-speed railways. The results revealed that some parts of the high-speed railways in the BTH plain had passed through or approached the land subsidence area; the maximum cumulative subsidence of the Beijing–Shanghai, Tianjin–Baoding and Shijiazhuang–Jinan high-speed railways reached 326 mm, 384 mm and 350 mm, respectively. The forecasting accuracy for land subsidence along high-speed railways was enhanced by the EMD-GBDT model. The Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) were 0.38 mm to 0.56 mm and 0.23 mm to 0.38 mm, respectively.

Mycobacterium tuberculosis possesses a dynamic cell envelope, which consists of a peptidoglycan layer, a mycolic acid layer, and an arabinogalactan polysaccharide. This envelope possesses a highly complex and unique structure representing a barrier that protects and assists the growth of M. tuberculosis and allows its adaptation to the host. It regulates the immune response of the host cells, causing their damage. Therefore, the cell envelope of M. tuberculosis is an attractive target for vaccine and drug development. The emergence of multidrug-resistant as well as extensively drug resistant tuberculosis and co-infection with HIV prevented an effective control of this disease. Thus, the discovery and development of new drugs is a major keystone for TB treatment and control. This review mainly summarizes the development of drug enzymes involved in the biosynthesis of the cell wall in M. tuberculosis, and other potential drug targets in this pathway, to provide more effective strategies for the development of new drugs.

Mitochondrial alternative oxidase 1a (AOX1a) plays an extremely important role in the critical node of seed viability during storage. However, the regulatory mechanism is still poorly understood. The aim of this study was to identify the regulatory mechanisms by comparing OsAOX1a-RNAi and wild-type (WT) rice seed during artificial aging treatment. Weight gain and time for the seed germination percentage decreased to 50% (P50) in OsAOX1a-RNAi rice seed, indicating possible impairment in seed development and storability. Compared to WT seeds at 100%, 90%, 80%, and 70% germination, the NADH- and succinate-dependent O2 consumption, the activity of mitochondrial malate dehydrogenase, and ATP contents all decreased in the OsAOX1a-RNAi seeds, indicating that mitochondrial status in the OsAOX1a-RNAi seeds after imbibition was weaker than in the WT seeds. In addition, the reduction in the abundance of Complex I subunits showed that the capacity of the mitochondrial electron transfer chain was significantly inhibited in the OsAOX1a-RNAi seeds at the critical node of seed viability. The results indicate that ATP production was impaired in the OsAOX1a-RNAi seeds during aging. Therefore, we conclude that mitochondrial metabolism and alternative pathways were severely inhibited in the OsAOX1a-RNAi seeds at critical node of viability, which could accelerate the collapse of seed viability. The precise regulatory mechanism of the alternative pathway at the critical node of viability needs to be further analyzed. This finding might provide the basis for developing monitoring and warning indicators when seed viability declines to the critical node during storage.

As ancient cities are spaces that represent the development of civilization, it is worth exploring and studying their characteristics and conceptions of land use. In this regard, the focus has turned to the issue of how to achieve the efficient mining of massive urban remote sensing data through human–computer collaboration. In this paper, a new intelligent method of analyzing urban land use characteristics and their cultural significance is proposed; it is feasible, effective, accurate, manageable, and portable. The method is based on a geographic information system (GIS) and a specific algorithm. The city plan was calibrated with the help of satellite remote sensing images and sites. By constructing the “urban element area acquisition and analysis model”, various operations for areas in the city plan were realized, including an area value calculation, land use structure calculation, area modulus analysis, area ratio analysis between areas, and determination of the cultural significance of numbers and ratios. Taking the Sui and Tang dynasties capital city of Chang’an as an example, we found the existence of a set of urban planning techniques through area modulus (standard area units) for the first time; it took the market area as the modulus A and the area of Daxing Palace as the expanded modulus 2A, made the area of important areas in the city an integer multiplied by the modulus value (for example, the overall scope of the city is 100A, the rectangular urban area is 90A, and the small city area is 10A), and made the key values and numerical ratios have a cultural significance (such as 4.5, 5.5, 10, 25, 30, 100, 12:10, 1.618:1, 9:5, 45:1, 2:1), reflecting the planning and design concept of the capital city, into which the ancient Chinese deliberately integrated “number, shape and meaning”. In addition, we carried out supplementary verification with the Roman city of Timgad and the Japanese city of Heijo-kyo, discovering that they also have design methods for area planning. We believe that land use planning can better meet the practical needs of urban resource distribution. Compared with urban form design, it might have chronological precedence. By setting the area modulus and the modulus value of each area, the grid-shaped city achieves the rational distribution of land and the establishment of order in an efficient way, and this thought and operation method greatly contributed to the advancement of ancient civilizations.

Abstract Bile acid metabolites have been increasingly recognized as pleiotropic signaling molecules that regulate cardiovascular functions, but their role in mesenchymal stromal cells (MSC)‐based therapy has never been investigated. It is found that overexpression of farnesoid X receptor (FXR), a main receptor for bile acids, improves the retention and cardioprotection of adipose tissue‐derived MSC (ADSC) administered by intramyocardial injection in mice with myocardial infarction (MI), which shows enhanced antiapoptotic, proangiogenic, and antifibrotic effects. RNA sequencing, LC‐MS/MS, and loss‐of‐function studies reveal that FXR overexpression promotes ADSC paracrine angiogenesis via Angptl4. FXR overexpression improves ADSC survival in vivo but fails in vitro. By performing bile acid‐targeted metabolomics using ischemic heart tissue, 19 bile acids are identified. Among them, cholic acid and deoxycholic acid significantly increase Angptl4 secretion from ADSC overexpressing FXR and further improve their proangiogenic capability. Moreover, ADSC overexpressing FXR shows significantly lower apoptosis by upregulating Nqo‐1 expression only in the presence of FXR ligands. Retinoid X receptor α is identified as a coactivator of FXR. It is first demonstrated that there is a bile acid pool in the myocardial microenvironment. Targeting the bile acid‐FXR axis may be a novel strategy for improving the curative effect of MSC‐based therapy for MI.

The automated detection of distress such as cracks or potholes is a key basis for assessing the condition of pavements and deciding on their maintenance. A fine-grained pavement distress-detection algorithm based on integrated data using a digital twin is proposed to solve the challenges of the insufficiency of high-quality negative samples in specific scenarios An asphalt pavement background model is created based on UAV-captured images, and a lightweight physical engine is used to randomly render 5 types of distress and 3 specific scenarios to the background model, generating a digital twin model that can provide virtual distress data. The virtual data are combined with real data in different virtual-to-real ratios (0:1 to 5:1) to form an integrated dataset and used to fully train deep object detection networks for fine-grained detection. The results show that the YOLOv5 network with the virtual-to-real ratio of 3:1 achieves the best average precision for 5 types of distress (asphalt pavement MAP: 75.40%), with a 2-fold and 1.5-fold improvement compared to models developed without virtual data and with traditional data augmentation, respectively, and achieves over 40% recall in shadow, occlusion and blur. The proposed approach could provide a more reliable and refined automated method for pavement analysis in complex scenarios.

Background: Renal diseases remain an increasing public health issue affecting millions of people. The kidney is a highly energetic organ that is rich in mitochondria. Numerous studies have demonstrated the important role of mitochondria in maintaining normal kidney function and in the pathogenesis of various renal diseases, including acute kidney injuries (AKI) and chronic kidney diseases (CKD). Summary: Under physiological conditions, fine-tuning mitochondrial energy balance, mitochondrial dynamics (fission and fusion processes), mitophagy, and biogenesis maintain mitochondrial fitness. While under AKI and CKD conditions, disruption of mitochondrial energy metabolism leads to increased oxidative stress. In addition, mitochondrial dynamics shift to excessive mitochondrial fission, mitochondrial autophagy is impaired, and mitochondrial biogenesis is also compromised. These mitochondrial injuries regulate renal cellular functions either directly or indirectly. Mitochondria-targeted approaches, containing genetic (microRNAs) and pharmaceutical methods (mitochondria-targeting antioxidants, mitochondrial permeability pore inhibitors, mitochondrial fission inhibitors, and biogenesis activators) are emerging as important therapeutic strategies for AKI and CKD. Key messages: Mitochondria play a critical role in the pathogenesis of AKI and CKD. This review provides an updated overview of mitochondrial homeostasis under physiological conditions and the involvement of mitochondrial dysfunction in renal diseases. Finally, we summarize the current status of mitochondria-targeted strategies in attenuating renal diseases.

Tuberculosis (TB) is a life-threatening infectious disease caused by Mycobacterium tuberculosis (M. tuberculosis). Timely diagnosis and effective treatment are essential in the control of TB. Conventional smear microscopy still has low sensitivity and is unable to reveal the drug resistance of this bacterium. The traditional culture-based diagnosis is time-consuming, since usually the results are available after 3–4 weeks. Molecular biology methods fail to differentiate live from dead M. tuberculosis, while diagnostic immunology methods fail to distinguish active from latent TB. In view of these limitations of the existing detection techniques, in addition to the continuous emergence of multidrug-resistant and extensively drug-resistant TB, in recent years there has been an increase in the demand for simple, rapid, accurate and economical point-of-care approaches. This review describes the development, evaluation, and implementation of conventional diagnostic methods for TB and the rapid new approaches for the detection of M. tuberculosis.

Hypoxia inducible factors (HIFs) and their regulatory hydroxylases the prolyl hydroxylase domain enzymes (PHDs) are the key mediators of the cellular response to hypoxia. HIFs are normally hydroxylated by PHDs and degraded, while under hypoxia, PHDs are suppressed, allowing HIF-α to accumulate and transactivate multiple target genes, including erythropoiesis, and genes participate in angiogenesis, iron metabolism, glycolysis, glucose transport, cell proliferation, survival, and so on. Aiming at stimulating HIFs, a group of small molecules antagonizing HIF-PHDs have been developed. Of these HIF-PHDs inhibitors (HIF-PHIs), roxadustat (FG-4592), daprodustat (GSK-1278863), vadadustat (AKB-6548), molidustat (BAY 85-3934) and enarodustat (JTZ-951) are approved for clinical usage or have progressed into clinical trials for chronic kidney disease (CKD) anemia treatment, based on their activation effect on erythropoiesis and iron metabolism. Since HIFs are involved in many physiological and pathological conditions, efforts have been made to extend the potential usage of HIF-PHIs beyond anemia. This paper reviewed the progress of preclinical and clinical research on clinically available HIF-PHIs in pathological conditions other than CKD anemia.

In this study, we propose a method that combines Bayesian network, structural equation modeling, and importance-performance analyses to evaluate and improve the service quality of crowded metros from the point of service components. First, service components that influence the service satisfaction of crowded metros are investigated, and 7 service components and 27 factors are collected from the perspective of metro daily operation. Correspondingly, 8,011 sample questioners are collected using both online (i.e. microblog and WeChat) and face-to-face survey methods. The usage of these service components is more practical for metro managers to improve service quality than the factor analysis methods used in previous studies. Second, a hybrid method combining Bayesian network and structural equation modeling is proposed to establish the relationship between service quality and these service components and factors. This hybrid method can learn the uncertain relationship directly from the data, explain the psychological element, and pinpoint the crucial service component. It is concluded that security check and waiting for boarding have the greatest effect on the overall satisfaction. With the help of importance-performance analyses, some practical suggestions (e.g., theme stations, women-only carriages, and one-day ticket) are proposed to optimize bottleneck service components and thus improve the service quality of daily metro operation. Further, heterogeneity of service quality satisfaction for various groups of respondents is discussed, which contributes to effective strategies for satisfaction improvement.

During daily subway operation, station closure has large impact on subway system organization and has received increasing attention. This article proposes an anomaly detection method based on ensemble algorithms to determine the range of station closure influence on passenger flow. Firstly, Ensemble Algorithm I is developed to identify the stations with passenger flow volume anomaly and origin-destination (OD) pairs with volume anomaly. Secondly, Ensemble Algorithm II is proposed to identify the OD pairs with travel time anomaly. Then, the spatial variation in passenger flow caused by station closure, i.e. shift of passenger flow to neighboring stations and shift of path flow, is analyzed, and the spatial-temporal influence range of station closure is determined. A case study of the Beijing subway system is performed to illustrate the validity of the proposed method.Compared with sub algorithm of ensemble learning and KNN algorithm, Ensemble Algorithm I and II are more robust and have less misjudgment.

ObjectiveClinical trials showed that sodium-glucose cotransporter 2 (SGLT2) inhibitors can improve non-alcoholic fatty liver disease (NAFLD). In this work, a meta-analysis of randomized controlled trials was conducted to evaluate the effect of SGLT2 inhibitors on type 2 diabetes mellitus (T2DM) with NAFLD.MethodsPubMed, Embase, Web of Science, and Cochrane Libraries were used for the systematic literature review to determine eligible studies. A randomized effect model was adapted to perform a meta-analysis on these eligible studies to estimate the combined effect sizes. Differences were expressed as the weighted average difference (WMD) of the continuous results and the 95% confidence interval (CI).ResultsTen randomized controlled trials with 573 participants were included. SGLT2 inhibitors significantly reduced the levels of alanine transaminase (WMD -5.36 [95% CI: -8.86, -1.85], p = 0.003) and Aspartate Transaminase (WMD -2.56 [95% CI: -3.83, -1.29], p

How to combine science and technology with the humanities in the research on ancient cities to reveal ancient peoples’ urban planning thoughts is worthy of in-depth study. The capitals of the Western Han dynasty as well as the Sui and Tang dynasties were some of the greatest cities in the world at the time. This paper takes them as its subjects and puts forward a method to study the spatial relationship between ancient cities and the natural environment by combining spatial information technology and cultural analysis. Firstly, satellite images, elevation maps, urban ichnographies, and literature materials were collected and sorted to deeply understand the cultural thoughts involved in ancient urban planning; based on this, key element points were marked and rechecked on the spot, and the above drawings were accurately superimposed by GIS technology to form a geographic information base that integrated multisource information. Then, Python was used to construct a “decision model of spatial relationship between urban elements and natural elements”, and rules as well as parameters were set through man–machine collaboration. The decision model was used to test the geographic information base, and the information of strong correlations between urban objects and natural objects was outputted. The drawings were exported after screening, and a visual expression was realized with Illustrator software. The research results indicated that this analysis method was feasible, effective, and easy to promote. The new archaeological discoveries included eight important line segments with a 9:6 proportional relationship (which represents the balance of Yin and Yang) and two important line segments with a 9:5 proportional relationship (which represents the supreme imperial power) in the capitals of the Western Han dynasty as well as the Sui and Tang dynasties, and 16 contraposition lines in a positive direction or oblique 45° direction (which reflects the close relationship between urban elements and natural elements). We consider that the two capitals were intentionally closely related to natural environments such as mountain peaks and valley entrances in the planning stage, and that proportions and scales with profound humanistic meaning were selected. The capital of the Sui and Tang dynasties was specially aligned with the capital of the Western Han dynasty in space. These characteristics embody ancient Chinese Confucian cultural thoughts such as the “integration of yang and yin”, “harmony between nature and humans”, the “supremacy of emperors”, and the “use of numbers and shapes to convey meaning”.

Multidrug resistance (MDR) of hepatocellular carcinoma (HCC) is a serious problem that directly hinders the effect of chemotherapeutics. In this study, we mainly explore the molecular mechanism of ROS-induced CD13 expression using hepatocarcinoma cells as the research object. We show that the drug of fluorouracil (5FU), epirubicin (EPI) and gemcitabine (GEM) can induce ROS generation, activate Ets2 and promote CD13 expression. Meanwhile, CD13 can activate NRF1 and up-regulate ROS scavenging genes transcription, such as SOD1, GPX1, GPX2 and GPX3, leading to down-regulation of intracellular ROS level and reducing the sensitivity of cells to chemotherapy agent. We also detected the anti-tumor effect of the combination therapy, CD13 inhibitor ubenimex and a variety of conventional anti-cancer drugs, such as 5FU, EPI, GEM, pemetrexed (Pem) and paclitaxel (PTX) were employed in combination. Ubenimex enhances the sensitivity of different chemotherapeutic agents and cooperates with chemotherapeutic agents to suppress tumor growth in vitro and in vivo. In general, overexpression of CD13 can lead to chemotherapy resistance, and CD13 inhibitor can reverse this effect. Combination of chemotherapy agent and ubenimex will become a potential treatment strategy for liver cancer resistance.

Reducing passenger waiting time and energy consumption through train scheduling can have a great impact on improving the quality of service and energy efficiency from an operational view. However, there is a lack of studies of timetable optimization for connecting different modes of rail transit while considering the passenger transfer demand. This research considered the connection between a one-direction metro timetable and a railway timetable. Based on the spatiotemporal distribution of the demand of passenger flow, the optimal metro timetable for transfer passengers in different planning horizons was determined by optimizing and adjusting the following headway, running time of sections, and dwell time at stations. We proposed a multi-objective programming model consisting of three objective functions to minimize energy consumption, passenger waiting time at stations and the waiting time of transfer passengers at transfer stations. We used a fuzzy multi-objective optimization algorithm to solve the multi-objective programming model and added different weight factors to the three objective functions to obtain three optimal timetables, namely, timetables for energy-savings (E-timetable), passenger waiting time (WT-timetable), and transfer passenger waiting time (TWT-timetable); these timetables maximize energy efficiency, the quality of passenger service, and the transfer efficiency respectively. Finally, two practical cases based on real-world operational data were used to demonstrate the performance of the proposed models. The results showed that the three optimized timetables met the different requirements of the decision-makers; the combined use of the three optimized timetables can be used to guide actual operations.

Train dispatching (TD) is at the forefront of all rail operations that transport passengers or goods. Recent technological advances and the explosion of digital data have introduced data-driven methods (DDMs) in rail operations. In this study, DDMs on the TD problem are briefly explored, focusing on relevant studies on delay distribution, delay propagation, and timetable rescheduling. Data-driven TD methods, including statistical methods (SM), graphical models (GM), and machine learning (ML) methods are reviewed. Then, key issues in establishing different data-driven models for the TD problem are addressed. Subsequently, ML methods are considered to be among the most promising DDMs that lead to innovative TD methods, relying on rich data obtained from train operations. This study emphasizes the potentials for designing new alternatives in the three key fields of interest and provides directions for further research on TD. Future research, including the ML-driven TD and intelligent TD, were discussed in this study.

Rail transit (RT) has been favored by passengers because it effectively alleviates the problems of dense population, housing shortages, small natural areas, and serious air pollution in urban centers. In this paper, we propose a framework that combines statistical analysis, fuzzy theory, and the technique for order preference by similarity to an ideal solution (TOPSIS) to evaluate the service quality of RT. First, the passenger perception of service quality is modeled as trapezoidal fuzzy numbers from the fuzzy theory, which solves the uncertainty problem of passenger perception that how factors affect service quality. Next, a case study that evaluates the service quality of the Beijing metro system is proposed using the fuzzy TOPSIS method. During the evaluation process, 8011 surveys are collected from 16 metro lines operated by Beijing Metro Operating Company Ltd. The evaluation results show that transfers, in-vehicle experience, and ticket purchases or recharges are the three factors that passengers find most unsatisfactory about metro travel and that need to be greatly improved in the future construction and management of metros. Furthermore, we analyze the stableness of the fuzzy TOPSIS method by the ranking change of service quality for a line from different comparison sets of metro lines. Finally, we provide suggestions and guidance for the optimization of RT infrastructure and investment.

The Allee effect is widespread among endangered plants and animals in ecosystems, suggesting that a minimum population density or size is necessary for population survival. This paper investigates the stability and pattern formation of a predator–prey model with nonlinear reactive cross-diffusion under Neumann boundary conditions, which introduces the Allee effect. Firstly, the ODE system is asymptotically stable for its positive equilibrium solution. In a reaction system with self-diffusion, the Allee effect can destabilize the system. Then, in a reaction system with cross-diffusion, through a linear stability analysis, the cross-diffusion coefficient is used as a bifurcation parameter, and instability conditions driven by the cross-diffusion are obtained. Furthermore, we show that the system (5) has at least one inhomogeneous stationary solution. Finally, our theoretical results are illustrated with numerical simulations.

Departure time choice is critical for subway passengers to avoid congestion during morning peak hours. In this study, we propose a Bayesian network (BN) model to capture departure time choice based on data learning. Factors such as travel time saving, crowding, subway fare, and departure time change are considered in this model. K2 algorithm is then employed to learn the BN structure, and maximum likelihood estimation (MLE) is adopted to estimate model parameters, according to the data obtained by a stated preference (SP) survey. A real-world case study of Beijing subway is illustrated, which proves that the proposed model has higher prediction accuracy than typical discrete choice models. Another key finding indicates that subway fare discount higher than 20% will motivate some passengers to depart 15 to 20 minutes earlier and release the pressure of crowding during morning peak hours.

Urban mobility pattern recognition has great potential in revealing human travel mechanism, discovering passenger travel purpose, and predicting and managing traffic demand. This paper aims to propose a data-driven method to identify metro passenger mobility patterns based on Automatic Fare Collection (AFC) data and geo-based data. First, Point of Information (POI) data within 500 meters of the metro stations are captured to characterize the spatial attributes of the stations. Especially, a fusion method of multisource geo-based data is proposed to convert raw POI data into weighted POI data considering service capabilities. Second, an unsupervised learning framework based on stacked auto-encoder (SAE) is designed to embed the spatiotemporal information of trips into low-dimensional dense trip vectors. In detail, the embedded spatiotemporal information includes spatial features (POI categories around the origin station and that around the destination station) and temporal features (start time, day of the week, and travel time). Third, a density-based clustering algorithm is introduced to identify passenger mobility patterns based on the embedded dense trip vectors. Finally, a case of Beijing metro network is used to verify the feasibility of the above methodology. The results show that the proposed method performs well in recognizing mobility patterns and outperforms the existing methods.

Immune response plays an important role in the pearl sac formation and pearl quality. However, there is little knowledge about the mode and mechanism of the immune responses in the pearl sac formation of the pearl mussel Hyriopsis cumingii. In this study, we monitored the process of pearl sac formation by histology examination for 21 days after grafting. The results showed that a large number of hemocytes aggregated in the pearl sac cavity on day 8 after grafting and provided organic substrate for the deposition of extracellular matrix and CaCO3 crystal and mediated the initiation of pearl forming on day 12 after grafting. These results revealed the important role of hemocytes on the early pearl sac and pearl formations. In the transcriptome analysis of pearl sac at the key time-points of day 0 and days 6, 8, 12 after grafting, the expression profiles of the immune-related genes revealed the immune response pattern of H. cumingii after grafting. The significant up-regulation in the hydrolytic enzymes, acute phase proteins, and antimicrobial peptides of humoral defense factors mRNA expression on day 6 after grafting suggested that these immune-related gene products were the main immune defense during the early wound healing; Meanwhile, the continuous mRNA up-regulation of antioxidant enzymes such as Cu-Zn SOD, Se-GPX, and tyrosinase in prophenoloxidase (proPO) system on days 8 and 12 suggested the important role of these immune effectors in oxidation-reduction on the later stage of pearl sac and pearl formations in H. cumingii. Moreover, the results of KEGG analysis of differentially expressed genes suggested the potential regulatory function of the signaling pathways of proPO system and complement system during pearl sac formation. These results provided valuable new insights into the roles and functions of the immune system in pearl sac and pearl formation.

Optimizing to increase the utilization ratio of regenerative braking energy reduces energy consumption, and can be done without increasing the deviation of train running time in one circle. The latter entails that the train timetable is upheld, which guarantees that the demand for passenger transport services is met and the quality of services in the urban rail transit system is maintained. This study proposes a multi-objective optimization model for urban railways with timetable optimization to minimize the total energy consumption of trains while maximizing the quality of service. To this end, we apply the principles and ideas of calculus to reduce the power of the velocity in the train energy consumption model. This greatly simplifies the complexity of the optimization model. Then, considering the conflicting requirements of decision-makers, weight factors are added to the objective functions to reflect decision-makers’ preferences for energy-saving and the quality of service. We adopt the nondominated sorting genetic algorithm-II (NSGA-II) to solve the proposed model. A practical case study of the Yizhuang urban railway line in Beijing is conducted to verify the effectiveness of the proposed model and evaluate the advantages of the optimal energy saving timetable (OEST) in comparison to the optimal quality of service timetable (OQOST). The results showed that the OEST reduced total energy consumption by 8.72% but increased the deviation of trains running time in one circle by 728 s. The total energy consumption was reduced by 6.09%, but there was no increase in the deviation of train running time in one circle with the OQOST.

At present, the existing dynamic OD estimation methods in an urban rail transit network still need to be improved in the factors of the time-dependent characteristics of the system and the estimation accuracy of the results. This study focuses on predicting the dynamic OD demand for a time of period in the future for an urban rail transit system. We propose a nonlinear programming model to predict the dynamic OD matrix based on historic automatic fare collection (AFC) data. This model assigns the passenger flow to the hierarchical flow network, which can be calibrated by backpropagation of the first-order gradients and reassignment of the passenger flow with the updated weights between different layers. The proposed model can predict the time-varying OD matrix, the number of passengers departing at each time, and the travel time spent by passengers, of which the results are shown in the case study. Finally, the results indicate that the proposed model can effectively obtain a relatively accurate estimation result. The proposed model can integrate more traffic characteristics than traditional methods and provides an effective and hierarchical passenger flow estimation framework. This study can provide a rich set of passenger demand for advanced transit planning and management applications, for instance, passenger flow control, adaptive travel demand management, and real-time train scheduling.

Congestion occurs and propagates in the stations of urban rail transit, which results in the impendent need to comprehensively evaluate the station performance. Based on complex network theory, a key station identification method is considered. This approach considers both the topology and dynamic operation states of urban rail transit network, such as degree, passenger demand, system capacity and capacity utilization. A case of Beijing urban rail transit is applied to verify the validation of the proposed method. It shows that the method can be helpful to daily passenger flow control and capacity enhancement during peak hours.

In this study, a mixed integer programming model is proposed to address timetable rescheduling problem under primary delays. The model considers timetable rescheduling strategies such as retiming, reordering, and adjusting stop pattern. A genetic algorithm-based particle swarm optimization algorithm is developed where position vector and genetic evolution operators are reconstructed based on departure and arrival time of each train at stations. Finally, a numerical experiment of Beijing-Shanghai high-speed railway corridor is implemented to test the proposed model and algorithm. The results show that the objective value of proposed method is decreased by 15.6%, 48.8%, and 25.7% compared with the first-come-first-service strategy, the first-schedule-first-service strategy, and the particle swarm optimization, respectively. The gap between the best solution obtained by the proposed method and the optimum solution computed by CPLEX solver is around 19.6%. All delay cases are addressed within acceptable time (within 1.5 min). Moreover, the case study gives insight into the correlation between delay propagation and headway. The primary delays occur in high-density period (scheduled headway closes to the minimum headway), which results in a great delay propagation.

A rapid and accurate determination method for total phenolic content is of great importance for controlling the quality of wine samples. A promising potentiometric detection approach, based on permanganate ion fluxes across ion-selective electrode membranes, is fabricated for measuring the total phenolic content of wine. The results show that the presence of phenols, such as gallic acid, leads to a potential increase for the potentiometric sensor. Additionally, the present sensor exhibits a linear potential response with the concentration range from 0.05 to 3.0 g/L with a detection limit of 6.6 mg/L calculated using gallic acid. These sensors also exhibit a fast response time, an acceptable reproducibility and long-term stability. These results indicate that the proposed potentiometric sensor can be a promising and reliable tool for the rapid determination of total phenolic content in wine samples.

A colorimetric immunoassay has been reported for prostate-specific antigen (PSA) detection with CuO nanoparticles (CuO NPs) as signal labels. The method is based on Cu2+-catalyzed oxidation of ascorbic acid (AA) by O2 to depress the formation of colored gold nanoparticles (AuNPs). Specifically, HAuCl4 can be reduced by AA to produce AuNPs in situ. In the presence of target, CuO NPs-labeled antibodies were captured via the sandwich-type immunoreaction. After dissolving CuO nanoparticles with acid, the released Cu2+ catalyzed the oxidation of AA by O2, thus depressing the generation of AuNPs. To demonstrate the accuracy of the colorimetric assay, the released Cu2+ was further determined by a fluorescence probe. The colorimetric immunoassay shows a linear relationship for PSA detection in the range of 0.1~10 ng/mL. The detection limit of 0.05 ng/mL is comparable to that obtained by other CuO NPs-based methods. The high throughput, simplicity, and sensitivity of the proposed colorimetric immunoassay exhibited good applicability for assays of serum samples.