Rationale: Klipple-Trenaunary Syndrome (KTS) complicated by frequent cellulitis of lower extremity seriously affects a patient quality of life. The hemodynamic characteristics of the disease are ...still unclear. Direct skin incision or puncture to remove malformed veins at the lesion site carries the risk of non-healing of the surgical incision. Our aim is to explore initial management strategies based on the hemodynamic characteristics of this disease. Patient concerns: A 29-year-old Manchu man was affected by KTS from childhood, characterized by an increase of the circumference and superficial varicose veins of the lower extremity. In the past 5 years, he suffered from frequent cellulitis in the left leg every 15 days or so. Diagnoses: KTS complicated by frequent cellulitis of lower extremity. Interventions: The clinical and hemodynamic characteristics of KTS were evaluated by Doppler ultrasonography (DUS) combined with CT venography (CTV), and foam sclerotherapy and postoperative elastic bandage compression were performed accordingly. Outcomes: Based on evaluations, the reason for frequent cellulitis was the continuous increase of venous hypertension in the calf caused by the malformed superficial vein and its penetrating vein. After 3 operations, the patient had no recurrence of cellulitis of the leg. Follow-up for 1 year showed no recurrence of left leg cellulitis. Lessons: This report emphasizes that foam sclerotherapy can significantly improve the clinical symptoms of KTS, such as cellulitis, and provide a safe skin environment for the implementation of other surgical methods, based on the evaluation of the pathological characteristics of KTS by DUS combined with CTV.
Receptor-interacting protein kinase 3 (RIPK3) functions as a central regulator of necroptosis, mediating signaling transduction to activate pseudokinase mixed lineage kinase domain-like protein ...(MLKL) phosphorylation. Increasing evidences show that RIPK3 contributes to the pathologies of inflammatory diseases including multiple sclerosis, infection and colitis. Here, we identified a novel small molecular compound Salt-inducible Kinases (SIKs) inhibitor HG-9-91-01 inhibiting necroptosis by targeting RIPK3 kinase activity. We found that SIKs inhibitor HG-9-91-01 could block TNF- or Toll-like receptors (TLRs)-mediated necroptosis independent of SIKs. We revealed that HG-9-91-01 dramatically decreased cellular activation of RIPK3 and MLKL. Meanwhile, HG-9-91-01 inhibited the association of RIPK3 with MLKL and oligomerization of downstream MLKL. Interestingly, we found that HG-9-91-01 also trigger RIPK3-RIPK1-caspase 1-caspase 8-dependent apoptosis, which activated cleavage of GSDME leading to its dependent pyroptosis. Mechanistic studies revealed that SIKs inhibitor HG-9-91-01 directly inhibited RIPK3 kinase activity to block necroptosis and interacted with RIPK3 and recruited RIPK1 to activate caspases leading to cleave GSDME. Importantly, mice pretreated with HG-9-91-01 showed resistance to TNF-induced systemic inflammatory response syndrome. Consistently, HG-9-91-01 treatment protected mice against Staphylococcus aureus-mediated lung damage through targeting RIPK3 kinase activity. Overall, our results revealed that SIKs inhibitor HG-9-91-01 is a novel inhibitor of RIPK3 kinase and a potential therapeutic target for the treatment of necroptosis-mediated inflammatory diseases.
Low probability of intercept (LPI) radars are widely used in modern electromagnetic environments due to their excellent anti-interception performance. However, this inevitably increases the ...difficulties in detecting and recognizing LPI radar signals for electronic support systems or radar warning receivers. To address this challenge, this paper proposes a multi-task neural network named JDMR-Net for joint detection and modulation recognition of LPI radar signals. The inherent multi-task learning capability obtains an improved performance through leveraging useful information across tasks. The JDMR-Net receives pulse sequence in I/Q format as input and is computational friendly compared to time-frequency image-based methods. The JDMR-Net consists of a local feature extraction module and a global similarity mining module. The local feature extraction module extracts modulation information within single pulse, while the global similarity mining module determines the similarity relationship among sequential pulses. The JDMR-Net can provide accurate time domain localization of detected pulses, and determine corresponding modulation type simultaneously. Through the multi-task framework, the processing steps of traditional processing chain are compressed efficiently and the two modules are highly parallelizable, making the proposed solution promising for on-line application with raw signal inputs. Extensive experiments on simulated and measured LPI signals demonstrate the effectiveness and robustness of the proposed method in terms of lower detectable signal to noise ratio (SNR) and low computational complexity.
This study carried out the fatigue tests of selective laser melting (SLM) 304L austenitic stainless steel (SS) made by different scanning speeds. The purpose is to deeply understand the ...microstructure, fatigue failure process and fatigue failure mechanism of SLMed 304L SS. For this purpose, the microstructure, surface roughness and porosity were tested by field emission scanning electron microscope (FESEM) and electron backscatter diffraction (EBSD), while the residual stress was obtained by μ-X360 residual stress analyzer. In addition, the fatigue failure process of SLMed 304L SS was in-situ monitored through acoustic emission (AE) technique and thermal imager. The results show that SLMed 304L SS has excellent fatigue performance. The ‘critical’ value is defined to distinguish the critical influence of surface roughness and porosity. In addition, the temperature rise caused by the stored energy deriving from the active dislocation motions is affected by the loading direction and scanning direction by regulating the dislocation motions during fatigue testing.
Exposure to antibiotics can result in not only ecotoxicity on aquatic organisms but also the development of antibiotic resistance. In the study, the ecotoxicity data and minimum inhibitory ...concentrations of the antibiotics were screened to derive predicted no-effect concentrations of ecological (PNECeco) and resistance development risks (PNECres) for 36 antibiotics in fresh surface waters of China. The derived PNECeco and PNECres values were ranged from 0.00175 to 2351 μg/L and 0.037–50 μg/L, respectively. Antibiotic ecological and resistance development risks were geographically widespread, especially in the Yongding River, Daqing River, and Ziya River basins of China. Based on the risk quotients, 11 and 14 of 36 target antibiotics were at high ecological risks and high resistance development risks in at least one basin, respectively. The higher tiered assessments provided more detailed risk descriptions by probability values and β-lactams (penicillin and amoxicillin) were present at the highest levels for ecological and resistance development risks. Although there was uncertainty based on the limited data and existing methods, this study can indicate the overall situation of the existing risk levels and provide essential insights and data supporting antibiotic management.
The symmetry principle has significant guiding value in vehicle dynamics modeling and motion control. In complex driving scenarios, there are problems of low accuracy and large time delay in the ...trajectory tracking control of unmanned ground vehicles. In order to solve this problem and improve the motion control of unmanned ground vehicles, a vehicle coordination control method based on chaotic particle swarm optimization (CPSO) and model predictive control (MPC) algorithms is proposed. To achieve coordinated control of vehicle trajectory tracking and yaw stability, a model predictive controller was designed with the objective of minimizing trajectory tracking errors and yaw stability tracking errors. The required front wheel angle and yaw torque control variables were obtained by solving nonlinear constraint optimization. At the same time, considering the problems of low computational efficiency, high solving time, and local optimization in model predictive control, a chaotic particle swarm optimization algorithm is introduced to solve the optimization constraint problem within model predictive control, thereby effectively improving the computational efficiency and accuracy of the model predictive trajectory tracking controller. The results show that compared with MPC, the multi-objective function optimization solution time and vehicle lane changing time of CPSOMPC improved by 24.51% and 7.21%, respectively, which indicates the coordinated control method that combines the CPSO and MPC algorithms can effectively improve trajectory tracking performance while ensuring vehicle lateral stability.
Verticillium
wilt (VW) caused by
Verticillium dahliae
is a devastating soil-borne disease that causes severe yield losses in cotton and other major crops worldwide. Here we conducted a ...high-throughput screening of isolates recovered from 886 plant rhizosphere samples taken from the three main cotton-producing areas of China. Fifteen isolates distributed in different genera of bacteria that showed inhibitory activity against
V. dahliae
were screened out. Of these, two
Pseudomonas
strains,
P. protegens
XY2F4 and
P. donghuensis
22G5, showed significant inhibitory action against
V. dahliae
. Additional comparative genomic analyses and phenotypical assays confirmed that
P. protegens
XY2F4 and
P. donghuensis
22G5 were the strains most efficient at protecting cotton plants against VW due to specific biological control products they produced. Importantly, we identified a significant efficacy of the natural tropolone compound 7-hydroxytropolone (7-HT) against VW. By phenotypical assay using the wild-type 22G5 and its mutant strain in 7-HT production, we revealed that the 7-HT produced by
P. donghuensis
is the major substance protecting cotton against VW. This study reveals that
Pseudomonas
specifically has gene clusters that allow the production of effective antipathogenic metabolites that can now be used as new agents in the biocontrol of VW.
Multi-function radars are sophisticated types of sensors with the capabilities of complex agile inter-pulse modulation implementation and dynamic work mode scheduling. The developments in MFRs pose ...great challenges to modern electronic reconnaissance systems or radar warning receivers for recognition and inference of MFR work modes. To address this issue, this article proposes an online processing framework for parameter estimation and change point detection of MFR work modes. At first, this article designed a fully-conjugate Bayesian Non-Parametric Hidden Markov Model with a designed prior distribution (agile BNP-HMM) to represent the MFR pulse agility characteristics. Then, the proposed framework is constructed by two main parts. The first part is the agile BNP-HMM model for automatically inferring the number of HMM hidden states and emission distribution of the corresponding hidden states. An error lower bound is derived for estimation performance and the proposed algorithm is shown to be closer to the bound compared with baseline methods. The second part combines the streaming Bayesian updating to facilitate computation, and designed an online work mode change detection framework based upon the weighted sequential probability ratio test. We demonstrate that the proposed framework is consistently highly effective and robust to baseline methods on diverse simulated radar signal data and real-life benchmark datasets. The source code is available at https://github.com/JiadiBao/Agile-BNP-HMM .
A theoretical analysis of proton transfer process for the symmetric systems with two intramolecular hydrogen bonds, bis-3,6-(2-benzoxazolyl)-pyrocatechol(BBPC) in hexane solvent, has been researched. ...In this study, we utilized ωB97X-D/ 6-311 + g (d,p) and B3LYP/6-31 + G(d) two procedures calculating the foremost bond length and bond angle, respectively. Our calculations demonstrate the two intramolecular hydrogen bonds were strengthened in S1 state, thus the proton transfer reaction can be facilitated. Furthermore, the calculated IR vibrational spectra confirmed hydrogen bonds were enhanced in S1 state. We found three local minima A B and C from the potential energy surfaces (PESs) on the S1 state, and the energy of B point and C point are identical. A new ESIPT mechanism has been proposed that was not equal to the previous conclusions. The new ESIPT mechanism elucidates that single proton transfer more likely occurs in the symmetric BBPC molecule in comparison with the double proton transfer reaction. And the frontier molecular orbitals(MOs) further illustrate the trend of ESIPT reaction.
Using the ultrafast pump-probe transient absorption spectroscopy, the femtosecond-resolved plasmon-exciton interaction of graphene-Ag nanowire hybrids is experimentally investigated, in the VIS-NIR ...region. The plasmonic lifetime of Ag nanowire is about 150 ± 7 femtosecond (fs). For a single layer of graphene, the fast dynamic process at 275 ± 77 fs is due to the excitation of graphene excitons, and the slow process at 1.4 ± 0.3 picosecond (ps) is due to the plasmonic hot electron interaction with phonons of graphene. For the graphene-Ag nanowire hybrids, the time scale of the plasmon-induced hot electron transferring to graphene is 534 ± 108 fs, and the metal plasmon enhanced graphene plasmon is about 3.2 ± 0.8 ps in the VIS region. The graphene-Ag nanowire hybrids can be used for plasmon-driven chemical reactions. This graphene-mediated surface-enhanced Raman scattering substrate significantly increases the probability and efficiency of surface catalytic reactions co-driven by graphene-Ag nanowire hybridization, in comparison with reactions individually driven by monolayer graphene or single Ag nanowire. This implies that the graphene-Ag nanowire hybrids can not only lead to a significant accumulation of high-density hot electrons, but also significantly increase the plasmon-to-electron conversion efficiency, due to strong plasmon-exciton coupling.
PDF
