The role of lysosomes as intermediates in betacoronavirus PHEV egress from nerve cells.

IMPORTANCE: Betacoronaviruses, including severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and mouse hepatitis virus (MHV), exploit the lysosomal exocytosis pathway for egress. However, whether all betacoronaviruses members use the same pathway to exit cells remains unknown. Here, we demonstrated that porcine hemagglutinating encephalomyelitis virus (PHEV) egress occurs by Arl8b-dependent lysosomal exocytosis, a cellular egress mechanism shared by SARS-CoV-2 and MHV. Notably, PHEV acidifies lysosomes and activates lysosomal degradative enzymes, while SARS-CoV-2 and MHV deacidify lysosomes and limit the activation of lysosomal degradative enzymes. In addition, PHEV release depends on V-ATPase-mediated lysosomal pH. Furthermore, this is the first study to evaluate ßCoV using lysosome for spreading through the body, and we have found that lysosome played a critical role in PHEV neural transmission and brain damage caused by virus infection in the central nervous system. Taken together, different betacoronaviruses could disrupt lysosomal function differently to exit cells.

Beauvericin suppresses the proliferation and pulmonary metastasis of osteosarcoma by selectively inhibiting TGFBR2 pathway.

Osteosarcoma (OS) patients, particularly those with distant metastasis, experience rapid progression and derive poor survival benefits from traditional therapies. Currently, effective drugs for treating patients with metastatic OS remain scarce. Here, we found that the cyclic hexadepsipeptide beauvericin (BEA) functioned as a new selective TGFBR2 inhibitor with potent antiproliferative and antimetastatic activities against OS cells. Functionally, BEA inhibited TGF-ß signaling-mediated proliferation, invasiveness, mesenchymal phenotype, and extracellular matrix remodeling of OS cells, and suppressed tumor growth and reduced pulmonary metastasis in vivo. Mechanistic investigation revealed that BEA selectively and directly bound to Asn 332 of TGFBR2 and inhibited its kinase activity, thereby suppressing the aggressive progression of OS cells. Together, our study identifies an innovative and natural selective TGFBR2 inhibitor with effective antineoplastic activity against metastatic OS and demonstrates that targeting TGFBR2 could be a potential therapeutic strategy for metastatic OS.

Zoledronic acid and thymosin α1 elicit antitumor immunity against prostate cancer by enhancing tumor inflammation and cytotoxic T cells.

BACKGROUND: Advanced or metastatic prostate cancer (PCa) is still an incurable malignancy with high lethality and a poor prognosis. Despite the remarkable success of immunotherapy against many types of cancer, most patients with PCa receive minimal benefit from current immunotherapeutic strategies, because PCa is an immune cold tumor with scarce T-cell infiltration in the tumor microenvironment. The aim of this study was to develop an effective immunotherapeutic approach for immune cold PCa tumors. METHODS: The therapeutic efficacy of androgen deprivation therapy (ADT) and zoledronic acid (ZA) plus thymosin α1 (Tα1) therapy was analyzed retrospectively in patients with advanced or metastatic PCa. The effects and mechanisms by which ZA and Tα1 regulated the immune functions of PCa cells and immune cells were evaluated by a PCa allograft mouse model, flow cytometric analysis, immunohistochemical and immunofluorescence staining assays, and PCR, ELISA, and Western blot analyses. RESULTS: In this study, clinical retrospective analysis revealed that ADT combined with ZA plus Tα1 improved the therapeutic outcomes of patients with PCa, which might be associated with an enhanced frequency of T cells. ZA and Tα1 treatment synergistically inhibited the growth of androgen-independent PCa allograft tumors, with increased infiltration of tumor-specific cytotoxic CD8+ T cells and enhanced tumor inflammation. Functionally, ZA and Tα1 treatment relieved immunosuppression in PCa cells, stimulated pro-inflammatory macrophages, and enhanced the cytotoxic function of T cells. Mechanistically, ZA plus Tα1 therapy blocked the MyD88/NF-κB pathway in PCa cells but activated this signaling in macrophages and T cells, altering the tumor immune landscape to suppress PCa progression. CONCLUSIONS: These findings uncover a previously undefined role for ZA and Tα1 in inhibiting the disease progression of immune cold PCa tumors by enhancing antitumor immunity and pave the way for the application of ZA plus Tα1 therapy as an immunotherapeutic strategy for treating patients with immunologically unresponsive PCa.

Driver Stress Detection Using Ultra-Short-Term HRV Analysis under Real World Driving Conditions.

Considering that driving stress is a major contributor to traffic accidents, detecting drivers' stress levels in time is helpful for ensuring driving safety. This paper attempts to investigate the ability of ultra-short-term (30-s, 1-min, 2-min, and 3-min) HRV analysis for driver stress detection under real driving circumstances. Specifically, the t-test was used to investigate whether there were significant differences in HRV features under different stress levels. Ultra-short-term HRV features were compared with the corresponding short-term (5-min) features during low-stress and high-stress phases by the Spearman rank correlation and Bland-Altman plots analysis. Furthermore, four different machine-learning classifiers, including a support vector machine (SVM), random forests (RFs), K-nearest neighbor (KNN), and Adaboost, were evaluated for stress detection. The results show that the HRV features extracted from ultra-short-term epochs were able to detect binary drivers' stress levels accurately. In particular, although the capability of HRV features in detecting driver stress also varied between different ultra-short-term epochs, MeanNN, SDNN, NN20, and MeanHR were selected as valid surrogates of short-term features for driver stress detection across the different epochs. For drivers' stress levels classification, the best performance was achieved with the SVM classifier, with an accuracy of 85.3% using 3-min HRV features. This study makes a contribution to building a robust and effective stress detection system using ultra-short-term HRV features under actual driving environments.

Effect of aging and rejuvenation on adhesion properties of modified asphalt binder based on AFM.

The adhesion between asphalt binder and aggregate is very important to the performance and durability of asphalt pavement. In order to explore the characterisation of modified asphalt binder in microstructure during aging and rejuvenation, the virgin asphalt binder and three kinds of modified asphalt binder (styrene-butadiene-styrene block copolymer (SBS), rubber powder and high viscosity and high elasticity [HVHE] modifier) in different aging and rejuvenation condition were prepared. The micromorphology and surface adhesion were measured by atomic force microscopy. The average roughness value was used as the index to evaluate the micromorphology of asphalt binder. The surface adhesion was used as the index to evaluate the adhesion properties of asphalt binder. Results show that the "bee" structure of SBS-modified asphalt binder increased slightly after long-term aging, and the recovery effect of aromatics oil was the closest to that of the unaged one. The rubber powder-modified asphalt binder and HVHE-modified asphalt binder showed the spot structure. And no matter for short-term aging or long-term aging, aromatics oil had the best recovery effect on micro morphology. The adhesion of the three modified asphalts would decrease gradually after aging. The effects of three kinds of rejuvenator on the adhesion of SBS-modified asphalt binder and rubber powder-modified asphalt binder were different. Rejuvenator, aromatic oil and warm mix asphalt mixture (WMA) additive could rejuvenate the loss of adhesion of HVHE-modified asphalt binder to a certain extent.

Evaluation Approach of Fracture Behavior for Asphalt Concrete with Different Aggregate Gradations and Testing Temperatures Using Acoustic Emission Monitoring.

Different aggregate gradations of asphalt concrete possess dissimilar skeleton structures, leading to diverse macroscopic and mechanical characteristics. Acoustic emission (AE) technology can realize real-time monitoring of the whole damage evolution process of materials. The objective of the present investigation was to demonstrate the fracture characteristics of asphalt concrete with three types of aggregate gradations, including dense-graded asphalt concrete (AC), stone mastic asphalt (SMA), and open-graded friction course (OGFC) under indirect tensile load on account of the acoustic emission (AE) technique. The Marshall compaction method was used to prepare specimens, and the indirect tensile test (IDT) and AE monitoring were conducted simultaneously at different temperatures. The corresponding AE parameters containing energy, cumulative energy, count, and cumulative count were adopted to characterize the fracture process of asphalt concrete with different aggregate gradations. The impact of temperature on the damage characteristics of asphalt concrete was also assessed. Test results indicated that the AE parameters could effectively classify the damage stages of asphalt concrete, and specimens with different aggregate gradations exhibited different AE characteristics during failure processes. The combination of AE parameters and cumulative AE parameters can accurately characterize the damage characteristics of asphalt concrete. SMA specimens possessed the best overall performance among these three types of asphalt concrete in terms of the variations in energy and cumulative energy at different temperatures. The findings obtained in this study can provide a practical AE-based evaluation approach for demonstrating the fracture mechanism of asphalt concrete with different aggregate gradations.

Fracture Characterization of Ultra-High Performance Concrete Notched Beams under the Influence of Different Material Factors Based on Acoustic Emission Technique.

Acoustic emission (AE) technology is widely used in structural health monitoring. Glass sand (GS) made from waste glass is a promising replacement aggregate for quartz sand (QS) in ultra-high performance concrete (UHPC). This paper addresses the effects of different factors including water-binder ratio, length of basalt fiber (BF) and ratio of GS replacing QS on the fluidity and flexural strength of UHPC notched beam under four-point flexural loads. Meanwhile, the fracture characteristics of UHPC notched beam were characterized through acoustic emission (AE) technique. The results show that water-binder ratio and replacement ratio of GS present a positive correlation with work performance of UHPC, while length of BF exhibits a negative one. The flexural strength of UHPC notched beams can be improved by the decrease of the water-binder ratio and fiber length. The effect of water-binder ratio on flexural strength is the most significant, while the addition of GS presents the minimum one. The fracture characteristics of UHPC notched beams could be favorably characterized by AE parameters. Through the analysis and comparison of the evolution of AE parameters, the differences in fracture properties of UHPC notched beams with different flexural strengths can be realized. Through this study, the fluidity and flexural performance of UHPC produced by replacing QS with GS were demonstrated, which is beneficial to the cleaner production of UHPC. Meanwhile, the AE technique presented great potential for fracture characterization of UHPC notched beam, which also provided a promising method for real-time monitoring of cracking in the diagnosis of UHPC structures.

Affective and Enjoyment Responses to Sprint Interval Exercise at Different Hypoxia Levels.

Benefits of performing sprint interval training (SIT) under hypoxic conditions on improving cardiorespiratory fitness and body composition have been well-documented, yet data is still lacking regarding affective responses to SIT under hypoxia. This study aimed to compare affective responses to SIT exercise under different oxygen conditions. Nineteen active males participated in three sessions of acute SIT exercise (20 repetitions of 6 s of all-out cycling bouts interspersed with 15 s of passive recovery) under conditions of normobaric normoxia (SL: PIO2 150 mmHg, FIO2 0.209), moderate hypoxia (MH: PIO2 117 mmHg, FIO2 0.154, simulating an altitude corresponding to 2500 m), and severe hypoxia (SH: PIO2 87 mmHg, FIO2 0.112, simulating an altitude of 5000 m) in a randomized order. Perceived exertions (RPE), affect, activation, and enjoyment responses were recorded before and immediately after each SIT session. There were no significant differences across the three conditions in RPE or the measurements of affective responses, despite a statistically lower SpO2 (%) in severe hypoxia. Participants maintained a positive affect valence and reported increased activation in all the three SIT conditions. Additionally, participants experienced a medium level of enjoyment after exercise as indicated by the exercise enjoyment scale (EES) and physical activity enjoyment scale (PACES). These results indicated that performing short duration SIT exercise under severe hypoxia could be perceived as pleasurable and enjoyable as performing it under normoxia in active male population.

Reliability Assessment of Deflection Limit State of a Simply Supported Bridge using vibration data and Dynamic Bayesian Network Inference.

Structural health monitoring (SHM) has been widely used in all kinds of bridges. It is significant to accurately assess the serviceability and reliability of bridge subjected to severe conditions by SHM technique. Bridge deflection as an essential evaluation index can reflect structural condition perfectly. In this study, an approach for deflection calculation and reliability assessment of simply supported bridge is presented. Firstly, a bridge deflection calculation method is proposed based on modal flexibility and Kriging method improved by artificial bee colony algorithm. Secondly, a dynamic Bayesian network is employed to evaluate the deflection reliability combined with monitoring results which include modal frequency, mode shape, environmental temperature, and humidity. A linear regression model is established to analyze the relationship between modal parameters and environmental factors. Thirdly, a simply supported bridge is constructed and monitored to verify the effectiveness of the proposed method. The results reveal that the proposed method can precisely calculate the bridge deflection. Finally, the time-dependent reliabilities of two cases are computed and the effects of monitoring factors on bridge deflection reliability are analyzed by sensitivity parameter. It indicates that the reliability is negatively correlated with temperature and more sensitive to mode shape than other three factors.

Experimental Investigation of the Mechanical and Durability Properties of Crumb Rubber Concrete.

Recycling waste tire rubber by incorporating it into concrete has become the preferred solution to dispose of waste tires. In this study, the effect of the volume content of crumb rubber and pretreatment methods on the performances of concrete was evaluated. Firstly, the fine aggregate and mixture were partly replaced by crumb rubber to produce crumb rubber concrete. Secondly, the mechanical and durability properties of crumb rubber concrete with different replacement forms and volume contents had been investigated. Finally, the crumb rubber after pretreatment by six modifiers was introduced into the concrete mixture. Corresponding tests were conducted to verify the effectiveness of pretreatment methods as compared to the concrete containing untreated crumb rubber. It was observed that the mechanical strength of crumb rubber concrete was reduced, while durability was improved with the increasing of crumb rubber content. 20% replacement of fine aggregate and 5% replacement of the total mixture exhibited acceptable properties for practical applications. In addition, the results indicated that the modifiers had a positive impact on the mechanical and durability properties of crumb rubber concrete. It avoided the disadvantage of crumb rubber concrete having lower strength and provides a reference for the production of modified crumb rubber concrete.

Reuse of Boron Waste as an Additive in Road Base Material.

The amount of boron waste increases year by year. There is an urgent demand to manage it in order to reduce the environmental impact. In this paper, boron waste was reused as an additive in road base material. Lime and cement were employed to stabilize the waste mixture. Mechanical performances of stabilized mixture were evaluated by experimental methods. A compaction test, an unconfined compressive test, an indirect tensile test, a modulus test, a drying shrinkage test, and a frost resistance test were carried out. Results indicated that mechanical strengths of lime-stabilized boron waste mixture (LSB) satisfy the requirements of road base when lime content is greater than 8%. LSB can only be applied in non-frozen regions as a result of its poor frost resistance. The lime-cement-stabilized mixture can be used in frozen regions when lime and cement contents are 8% and 5%, respectively. Aggregate reduces the drying shrinkage coefficient effectively. Thus, aggregate is suggested for mixture stabilization properly. This work provides a proposal for the management of boron waste.

Unsupervised performance evaluation strategy for bridge superstructure based on fuzzy clustering and field data.

Performance evaluation of a bridge is critical for determining the optimal maintenance strategy. An unsupervised bridge superstructure state assessment method is proposed in this paper based on fuzzy clustering and bridge field measured data. Firstly, the evaluation index system of bridge is constructed. Secondly, a certain number of bridge health monitoring data are selected as clustering samples to obtain the fuzzy similarity matrix and fuzzy equivalent matrix. Finally, different thresholds are selected to form dynamic clustering maps and determine the best classification based on statistic analysis. The clustering result is regarded as a sample base, and the bridge state can be evaluated by calculating the fuzzy nearness between the unknown bridge state data and the sample base. Nanping Bridge in Jilin Province is selected as the engineering project to verify the effectiveness of the proposed method.