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Polycyclic aromatic hydrocarbons (PAHs) are closely related to the occurrence of cardiovascular diseases, nevertheless the toxicological mechanism remains ambiguous. To verify whether PAHs exposure leads to cardiovascular senescence, 8-week-old male sprague–dawley rats and primary human umbilical vein endothelial cells were exposed to different concentrations of 16 priority-controlled PAHs for 90 d and 48 h respectively. In in vitro study, PAHs exposure promoted aryl hydrocarbon receptor (AhR) activation, and then directly or indirectly inhibited SIRT6 expression leading to telomere dysfunction, which further caused DNA damage and subsequently promoted endothelial cells senescence. But the treatment of CH-223191 (an AhR inhibitor) rescued the aging phenotypes induced by PAHs, suggesting that AhR plays an important role in PAHs-induced endothelial cells senescence. In in vivo study, PAHs exposure raised AhR expression, affected SIRT6-related aging signaling pathway, and induced myocardial and vascular remodeling in rats. Molecular dynamics simulations demonstrated that, in addition to benzo[a]pyrene-7,8-diol-9,10-epoxide (the mediate metabolite of benzo[a]pyrene), typical parent PAHs (phenanthrene, benzo[a]pyrene) can directly bind to known DNA strand binding sites of SIRT6 through hydrophobic force, which was further validated by electrophoretic mobility shift assay. All above indicates for the first time that in addition to classical AhR dependent pathway, parent PAHs may affect DNA damage response and telomere maintenance function of SIRT6, which is a new mechanism of PAHs induced cardiovascular senescence.

The typical clinical signs of Nocardia seriolae infection include white nodules, ranging from 0.1 to 10 mm in diameter, distributed across various internal organs. However, the structural composition of nodules of different sizes remains unexplored. In this study, natural cases of largemouth bass (Micropterus salmoides) were collected, and pathogenic bacteria were isolated and confirmed through a re-infection experiment. The isolated bacteria were identified as N. seriolae through 16S rRNA and gyrB gene sequencing. Healthy largemouth bass were infected with the isolate using an immersion infection and observed continuously over 56 days. Samples were successfully obtained from the incubation, prodromal, symptomatic, and convalescent phases, allowing for gross, histological, and ultrastructural observations of nodular lesion progression. Results demonstrated two types of nodular lesions: necrotic foci and granulomas. Macroscopically visible nodules larger than 1 mm, observed primarily in the liver, spleen, kidney, and muscle tissues of moribund fish, exhibited coagulative necrosis and were identified as the principal cause of mortality. Conversely, granulomas, with diameters less than 1 mm, were consistently present in the spleen, kidney, and liver during the symptomatic and convalescent phases.

In this study, carbon nanotube (CNT)/carbon nanofiber (CNF) composite electrothermal films were prepared by electrospinning, and the effects of the CNT content and carbonization temperature on the electrothermal properties of the CNT/CNF composite films were investigated. The experimental results demonstrated that the conductivity of the CNT/CNF composite electrothermal film (0.006–6.89 S/cm) was directly affected by the CNT content and carbonization temperature. The electrothermal properties of the CNT/CNF positively correlated with the CNT content, carbonization temperature, and applied voltage. The surface temperature of CNT/CNF can be controlled within 30–260 °C, and continuously heated and cooled 100 times without any loss. The convective heat transfer with air is controllable between 0.008 and 31.75. The radiation heat transfer is controllable between 0.29 and 1.92. The prepared CNT/CNF exhibited a heat transfer efficiency of up to 94.5%, and melted a 1 cm thick ice layer within 3 min by thermal convection and radiation alone.

Abstract Many types of microorganisms, including SARS-CoV-2, can spread through aerosols. Indoor medical environments are abundant in bioaerosols, which can cause infections among medical staff members and patients in hospitals. Given the ongoing COVID-19 pandemic, using a steady-state displacement air purification system may reduce the spread of SARS-CoV-2 and other microorganisms. In this study, we analyzed the purification effect of the steady-state displacement air purification system on bioaerosols in the bronchoscopy room of the hospital. In particular, bioaerosols were collected from the bronchoscopy room at different periods from April to May 2021. Among them, the microorganisms contained in the bioaerosol were identified using next-generation sequencing (NGS) and culture and strain identification. During the experiment, we took 5 sampling points to collect the bioaerosols. The total purification efficiency was 88.0% (NGS) and 87.5% (microbial culture count and identification). The results were significantly different between the purified and unpurified groups. In an occupant environment in the bronchoscopy room, the steady-state displacement air purification system exerted a favorable removal effect on the bioaerosols. Such purification efficiency may help prevent the in-hospital spread of COVID-19 and various infectious diseases.

IntroductionAnaerobic ammonium oxidation (anammox) plays a vital role in the global nitrogen cycle by oxidizing ammonium to nitrogen under anaerobic environments. However, the existence, abundance, and diversity of anammox bacteria between different temperatures are less studied, particularly in purple paddy soils.Methods13C-DNA stable-isotope probe combined with Illumina MiSeq high-throughput sequencing was employed to explore soil abundance and diversity of anammox bacteria. In doing so, 40–60 cm depth soils from typical purple paddy soils in Chongqing, southwest China, were cultured under 12CO2-labeled and 13CO2-labeled at 35°C, 25°C, 15°C, and 5°C for 56 days.Results and DiscussionAnammox bacteria were not labeled at all by 13CO2 at 5°C. The highest abundance of anammox bacteria was found at 25°C (3.52 × 106~3.66 × 106 copies·g−1 dry soil), followed by 35°C and 15°C (2.01 × 106~2.37 × 106 copies·g−1 dry soil) and almost no increase at 5°C. The relative abundance of Candidatus Jettenia sp. was higher at 25°C and 15°C, while Candidatus Brocadia sp. was higher at 35°C and 5°C. Our results revealed differences in anammox bacteria at different temperatures in purple paddy soils, which could provide a better understanding of soil N cycling regulated by anammox bacteria.

The design of railway alignment and station locations involves two intertwined problems, which makes it a complex and time-consuming task. Especially in mountainous regions, the large 3-dimensional (3D) search spaces, complex terrain conditions, coupling constraints and infinite numbers of potential alternatives of this problem pose many challenges. However, most current optimization methods emphasize either alignment optimization or station locations optimization independently. Only a few methods consider coordinated optimization of alignment and stations, but optimize them sequentially. This paper proposes a concurrent optimization method based on a 3-dimensional distance transform algorithm (3D-DT) to solve this problem. It includes the following components: (1) To optimize the location of stations within specified spacing intervals, a novel perceptual search strategy is proposed and incorporated into the basic 3D-DT optimization process. (2) A combined-alignment-station 3D search neighboring mask is developed and employed to search for both the alignment and stations. In order to implement the perceptual process, two additional kinds of 3D reverse perceptual neighboring masks are also developed and employed in the algorithm. (3) Multiple coupling constraints between alignment and stations are also formulated and addressed during the search process. In this study, the effectiveness of the method is verified through a real-world case study in a complex mountainous region. The optimization results show that the proposed method can find high-quality alternatives satisfying multiple coupling constraints.

In this paper, the fixed-time synchronization problem for a class of memristive neural networks with discontinuous neuron activation functions and mixed time-varying delays is investigated. With the help of the fixed-time stability theory, under the framework of Filippov solution and differential inclusion theory, several new and useful sufficient criteria for fixed-time synchronization are obtained by designing two types of energy-saving and simple controllers for the considered systems. Compared with the traditional fixed-time synchronization controller, the controllers used in this paper only have one power exponent term, which is a function of the system state error rather than a constant. Moreover, some previous relevant works are especially improved. Finally, two numerical examples are given to show the correctness and the effectiveness of the obtained theoretical results.

A railway track gradually deviates from the originally designed vertical alignment in the operation. To ensure the safety and comfort, railway maintenance department must periodically recreate vertical alignment and calibrate existing track to it. The recreated alignment should be as close as possible to the measured points along the existing railway track, while satisfying multiple constraints. A vertical alignment consists of tangents and curves. Identifying the geometric element attribution of the measured points accurately and recreating the vertical alignment efficiently and accurately with all the constraints satisfied are the key problems. Existing methods need manual assistance and few constraints are considered. This paper proposes an automatic global iterations method considering multiple constraints. Firstly, geometric elements are identified based on the change rate of gradient and are set as initial values for the iterations. Then, the geometric elements are fitted iteratively. In each iteration, all the tangents are fitted simultaneously followed by the fitting of all vertical curves and the constraints are handled while the geometric elements are fitted. The attributions of all points are adjusted after each iteration. If the attributions of all the points are consistent with the ranges of fitted geometric elements, the iteration terminates. A software is developed based on this method, and applications demonstrate this method can identify all geometric elements automatically and recreate an optimized vertical alignment while satisfying all the constraints.