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BACKGROUND: The main objective of this study was to predict the status of blood and the occurrence of lower limb deep vein thrombosis (DVT) after total knee arthroplasty(TKA) by means of mean platelet volume (MPV) combined with thromboelastography (TEG). METHODS: We collected 180 patients who underwent unilateral total knee arthroplasty between May 2015 and March 2022, and the patients were divided into DVT group and control group according to whole-leg ultrasonography on the seventh postoperative day. Blood count and TEG were performed on the day before surgery, the first day after surgery and the seventh day respectively. Multifactorial analysis was used to investigate whether the relevant parameters were independent predictors of DVT after TKA. RESULTS: MPV has the strongest correlation with the maximum amplitude (MA), followed by alpha-angle; MPV and alpha-angle on the first postoperative day are independent predictors of DVT. MPV in patients with thrombosis tends to rise and then fall in the perioperative period. The optimal threshold for MPV to predict thrombosis is 10.85 fL and the area under the ROC curve is 0.694, The area under the ROC curve increases to 0.815 using MPV combined with alpha-angle. In addition, MA, α-angle, composite coagulation index (CI) and MPV were all statistically higher in the DVT group than in the control group (p < 0.001). CONCLUSION: MPV is a predictor of DVT after TKA. It can reflect the hypercoagulable state of blood after surgery; Combination of MPV and alpha-angle on the first day after surgery in patients with TKA improves predictive power of DVT.

BACKGROUND: In China, the current status of clinical treatment of eLVO and the factors affecting its long-term prognosis are unclear. OBJECTIVE: This study aims to explore the predictive factors of functional outcomes at one year in patients of acute ischemic stroke with emergent large vessel occlusion (eLVO). METHODS: We retrospectively collected 536 patients who underwent treatments for eLVO. Primary outcomes included one-year functional outcomes and delayed functional independence (DFI). The logistic regression was performed to predict the primary outcome. RESULTS: 431 (85%) survivors participated in the one-year follow-up. In the multivariate logistic analysis adjusted for baseline characteristics, the following factors were found to be significant predictors of functional dependence at one year: old age (aOR = 1.042, 95% CI=1.01-1.076, p = 0.011), low Alberta stroke program early CT score (ASPECTS) (aOR = 0.791, 95% CI=0.671-0.933, p = 0.005), unsuccessful reperfusion (aOR = 0.168, 95% CI=0.048-0.586, p = 0.005), poor medication compliance (aOR = 0.022, 95% CI=0.007-0.072, p

Traditional joint-link robots have been widely used in production lines because of their high precision for single tasks. With the development of the manufacturing and service industries, the requirement for the comprehensive performance of robotics is growing. Numerous types of bio-inspired robotics have been investigated to realize human-like motion control and manipulation. A study route from inner mechanisms to external structures is proposed to imitate humans and animals better. With this idea, a brain-inspired intelligent robotic system is constructed that contains visual cognition, decision-making, motion control, and musculoskeletal structures. This paper reviews cutting-edge research in brain-inspired visual cognition, decision-making, motion control, and musculoskeletal systems. Two software systems and a corresponding hardware system are established, aiming at the verification and applications of next-generation brain-inspired musculoskeletal robots.

Single-cell interrogation with the solid-state nanoprobes enables understanding of the linkage between cellular behavior and heterogeneity. Herein, inspired by the charge property of the organic molecular probe (OMP), a generic ionic current rectification (ICR) single-cell methodology is established, exemplified by subcellular detection of glutathione (GSH) with high selectivity, sensitivity, and recyclability. The as-developed nanosensor can transduce the subcellular OMP-GSH interaction via a sensitive ionic response, which stems from the superior specificity of OMP and its essential charge property. In addition, the nanosensor exhibits good reversibility, since the subsequent tandem reaction after the recognition can well recover the sensing surface. Given the diverse structures and tailorable charge properties of OMP, this work underpins a new and general method of OMP-based ICR single-cell analysis.

Semiconductor metal-organic frameworks (MOFs) and heterojunctions have gained increasing attention in many fields, yet their full potential remains largely unexplored. Advanced optobioelectronics are envisioned to create more opportunities for innovative biomedical applications. This study reports a UiO-66-NH

A unique poly(amido amine) (PAMAM)/polymer dots (Pdots)/NiO heterostructure is developed for photocathodic detection of tyrosinase (TYR), which is applicable to TYR detection in actual human serum samples.

In this work, a method to improve the surge current capability of silicon carbide (SiC) merged PiN Schottky (MPS) diodes is presented and investigated via three-dimensional electro-thermal simulations. When compared with conventional MPS diodes, the proposed structure has a more uniform current distribution during bipolar conduction due to the help of the continuous P+ surface, which can avoid the formation of local hot spots during the surge process. The Silvaco simulation results show that the proposed structure has a 20.29% higher surge capability and a 15.06% higher surge energy compared with conventional MPS diodes. The bipolar on-state voltage of the proposed structure is 4.69 V, which is 56.29% lower than that of conventional MPS diodes, enabling the device to enter the bipolar mode earlier during the surge process. Furthermore, the proposed structure can suppress the occurrence of “snapback” phenomena when switching from the unipolar the bipolar operation mode. In addition, the analysis of the surge process of MPS diodes is carried out in detail.

Endometriosis is a benign gynecological disease with the feature of estrogen dependence and inflammation. The function of autophagy and the correlation with inflammation were not yet revealed.Autophagosomes were detected by transmission electron microscopy. Gene Expression Omnibus (GEO) database was referred to analyze the expression of autophagy-related genes. Quantification of mRNA and protein expression was examined by qRT-PCR and Western Blot. Immunohistochemistry was performed to explore the expression of proteins in tissues. The mouse model of endometriosis was performed to analyze the autophagic activity and effect of LXA4.The expression of autophagy-related genes in endometriotic lesions were unusually changed. The number of autophagosomes and LC3B-II expression was diminished, and p62 was increased in ectopic lesions from both patients and mice. Interleukin 1β (IL1β) attenuated the expression of LC3B and promoted the level p62. The autophagy activator MG-132 upregulated the expression of LC3B and reduced IL1β, IL6, and p62. LXA4 reversed the inhibitory effect of IL1β on the expression of LC3B and p62, and blocking the receptor of LXA4 AhR (aryl hydrocarbon receptor) resulted in the incapacitation of LXA4 to influence the effect of IL1β. LXA4 depressed the phosphorylation of AKT and mTOR to against IL1β, and blocking AhR negatively regulated the effect of LXA4 on AKT/mTOR pathway. LXA4 reduced the ectopic lesions and the expression of IL1β and p62, but enhanced LC3B-II in endometriotic mouse models.In endometriosis, increased inflammation of ectopic lesions prominently depresses autophagy. LXA4 could regulate autophagy by suppressing inflammatory response through AhR/AKT/mTOR pathway.

Coronavirus disease 2019 (COVID-19) remains a serious global threat. The metabolic analysis had been successfully applied in the efforts to uncover the pathological mechanisms and biomarkers of disease severity. Here we performed a quasi-targeted metabolomic analysis on 56 COVID-19 patients from Sierra Leone in western Africa, revealing the metabolomic profiles and the association with disease severity, which was confirmed by the targeted metabolomic analysis of 19 pairs of COVID-19 patients. A meta-analysis was performed on published metabolic data of COVID-19 to verify our findings. Of the 596 identified metabolites, 58 showed significant differences between severe and nonsevere groups. The pathway enrichment of these differential metabolites revealed glutamine and glutamate metabolism as the most significant metabolic pathway (Impact = 0.5; -log10P = 1.959). Further targeted metabolic analysis revealed six metabolites with significant intergroup differences, with glutamine/glutamate ratio significantly associated with severe disease, negatively correlated with 10 clinical parameters and positively correlated with SPO

The past decade has witnessed a rapid progress in asymmetric C–H activation. However, the enantioselective C–H alkoxylation and amination with alcohols and free amines remains elusive. Herein, we disclose the first enantioselective dehydrogenative C–H alkoxylation and amination enabled by a simple cobalt/salicyloxazoline (Salox) catalysis. The use of cheap and readily available cobalt(II) salts as catalysts and Saloxs as chiral ligands provides an efficient method to access P-stereogenic compounds in excellent enantioselectivities (up to >99% ee). The practicality of this protocol is demonstrated by gram-scale preparation and further derivatizations of the resulting P-stereogenic phosphinamides, which offering a flexible asymmetric alternative to access P-stereogenic mono- and diphosphine chiral ligands. Preliminary mechanistic studies on the enantioselective C–H alkoxylation reaction suggest that a cobalt(III/IV/II) catalytic cycle might be involved.

The past decade has witnessed a rapid progress in asymmetric C-H activation. However, the enantioselective C-H alkoxylation and amination with alcohols and free amines remains elusive. Herein, we disclose the first enantioselective dehydrogenative C-H alkoxylation and amination enabled by a simple cobalt/salicyloxazoline (Salox) catalysis. The use of cheap and readily available cobalt(II) salts as catalysts and Saloxs as chiral ligands provides an efficient method to access P-stereogenic compounds in excellent enantioselectivities (up to99 % ee). The practicality of this protocol is demonstrated by gram-scale preparation and further derivatizations of the resulting P-stereogenic phosphinamides, which offering a flexible asymmetric alternative to access P-stereogenic mono- and diphosphine chiral ligands. Preliminary mechanistic studies on the enantioselective C-H alkoxylation reaction suggest that a cobalt(III/IV/II) catalytic cycle might be involved.

Compared with bottom-fixed wind turbines, the supporting platform of a floating offshore wind turbine has a larger range of motion, so the gyroscopic effects of the system will be more obvious. In this paper, the mathematical analytic expression of the gyroscopic moment of a floating offshore wind turbine is derived firstly. Then, FAST software is utilized to perform a numerical analysis on the model of a spar-type horizontal axis floating offshore wind turbine, OC3-Hywind, so as to verify the correctness of the theoretical analytical formula and take an investigation on the characteristics of gyroscopic effect. It is found that the gyroscopic moment of the horizontal axis floating offshore wind turbine is essentially caused by the vector change of the rotating rotor, which may be due to the pitch or yaw motion of the floating platform or the yawing motion of the nacelle. When the rotor is rotating, the pitch motion of the platform mainly excites the gyroscopic moment in the rotor’s yaw direction, and the yaw motion of the platform largely excites the rotor’s gyroscopic moment in pitch direction, accordingly. The results show that the gyroscopic moment of the FOWT is roughly linearly related to the rotor’s inertia, the rotor speed, and the angular velocity of the platform motion.

Design of floating offshore wind turbines (FOWTs) needs reliable and innovative technologies to overcome the challenges on how to better predict the dynamic responses in terms of aero-hydro-servo-elastic disciplines. This paper aims to demonstrate the optimized prediction of the dynamic response of FOWTs by Simulation annealing diagnosis algorithm (SADA). SADA is an Artificial Intelligence technology-based method, which utilizes the advantages of numerical simulation, basin experiment and machine learning algorithms. The actor network in deep deterministic policy gradient (DDPG) is adopted to take actions to adjust the Key disciplinary parameters (KDPs) in each loop according to the feedback of 6DOF motions of platform in dynamic response analysis. The results demonstrated that the mean values of the platform’s motions and rotor axial thrust force could be predicted with higher accuracy. On this basis, other physical quantities that designers are more concerned about but cannot be obtained from experiments and actual measurements will be predicted by SADA with more credibility. This SADA method differs from traditional supervised learning applications in renewable energy, which do not need to be provided physical quantities with strong direct correlation. All targets can be artificially set for SADA to obtain a better self-learning performance. In general, designers can use SADA to get a more accurate and optimized prediction of the dynamic response of FOWTs, especially those physical quantities that cannot be directly obtained through the basin experiments.

Previous methods on Co

Due to the dissimilar scaling issues, the conventional experimental method of FOWTs can hardly be used directly to validate the full-scale global dynamic responses accurately. Therefore, it is of absolute necessity to find a more accurate, economic and efficient approach, which can be utilized to predict the full-scale global dynamic responses of FOWTs. In this paper, a literature review of experimental-numerical methodologies and challenges for FOWTs is made. Several key challenges in the conventional basin experiment issues are discussed, including scaling issues; coupling effects between aero-hydro and structural dynamic responses; blade pitch control strategies; experimental facilities and calibration methods. Several basin experiments, industrial projects and numerical codes are summarized to demonstrate the progress of hybrid experimental methods. Besides, time delay in hardware-in-the-loop challenges is concluded to emphasize their significant role in real-time hybrid approaches. It is of great use to comprehend these methodologies and challenges, which can help some future researchers to make a footstone for proposing a more efficient and functional hybrid basin experimental and numerical method.

The development of innovative synthetic polymer systems to overcome the trade-offs between the polymer's depolymerizability and performance properties is in high demand for advanced material applications and sustainable development. In this contribution, we prepared a class of aromatic cyclic esters (M1-M5) from thiosalicylic acid and epoxides by facile one-pot synthesis. Ring-opening polymerization of Ms afforded aromatic polyesters P(M)s with high molecular weights and narrow dispersities. The physical and mechanical properties of P(M)s can be modulated by stereocomplexation and regulation of the side-chain flexibility of the polymers, ultimately achieving high-performance properties such as high thermal stability and crystallinity (T

A transfer reaction and cluster-decay experiment, C( O, Mg α+ Ne)α, was performed at a beam energy of 96 MeV. Both recoil and decay α particles were detected in coincidence, allowing us to deduce the energy-momentum of a Ne fragment. A number of resonant states of Mg were reconstructed up to an excitation energy of approximately 30 MeV. Owing to the experimentally achieved excellent resolutions of the Q-value and excitation-energy spectra, the relative decay widths for each resonant state in Mg to various final states of Ne were extracted, along with the total decay width. The obtained results provide good testing ground for theoretical descriptions of multiple clustering configurations in Mg.

We demonstrate a hybrid Si photodetector structure by employing an additional layer of fluorescent carbon quantum dot (CQD) nanoparticles constructed on the surface of a Si positive-intrinsic-negative (PIN) photodetector. The experimental studies reveal that the optimized hybrid device can efficiently enhance short-wavelength range responsibility between 300 nm to 600 nm without inducing any deteriorated photodetection performance beyond the short-wavelength region, and thereby achieve broadband sensitivity across the UV–vis-NIR spectra region. The measured photoresponsivity of the optimized device can achieve ∼0.088 A W−1 (@500 nm), which was ∼25% higher than that of a commercial blank PIN Si photodetector.

Cathelicidins are an important antimicrobial peptide family and are expressed in many different vertebrates. They play an important role in the innate immune system of the host. However, amphibian cathelicidins are poorly understood. In this study, the cDNA of the cathelicidin gene was obtained from the skin transcriptome of tiger frog (Hoplobatrachus rugulosus). The predicted amino acid sequence of tiger frog cathelicidin (HR-CATH) comprises a signal peptide, a cathelin domain, and a mature peptide. The HR-CATH amino acid sequence alignment with other frog cathelicidins showed that the functional mature peptide is highly variable in amphibians, whereas the cathelin domain is conserved. A phylogenetic tree analysis showed that HR-CATH is most closely related to cathelicidin-NV from Nanorana ventripunctata. HR-CATH was chemically synthesized and its in vitro activity was determined. It had high antibacterial activity against Vibrio parahaemolyticus, Staphylococcus aureus, and the pathogenic bacterium Aeromonas hydrophila. HR-CATH damaged the cell membrane integrity of A. hydrophila according to a lactate dehydrogenase release assay and was able to hydrolyze the genomic DNA from A. hydrophila in a dose-dependent manner. Furthermore, in RAW264.7 cells (mouse leukemic monocyte/macrophage cell line), HR-CATH induced chemotaxis and enhanced respiratory burst. Our study shows that amphibian cathelicidin has antimicrobial activity and an immunomodulatory effect on immune cells.

Floating offshore wind turbines (FOWTs) still face many challenges on how to better predict the dynamic responses. Artificial intelligence (AI) brings a new solution to overcome these challenges with intelligent strategies. A new AI technology-based method, named SADA, is proposed in this paper for the prediction of dynamic responses of FOWTs. Firstly, the methodology of SADA is introduced with the selection of Key Disciplinary Parameters (KDPs). The AI module in SADA was built in a coupled aero-hydro-servo-elastic in-house programDARwindand the policy decision is provided by the machine learning algorithms deep deterministic policy gradient (DDPG). Secondly, a set of basin experimental results of a Hywind Spar-type FOWT were employed to train the AI module. SADA weights KDPs by DDPG algorithms' actor network and changes their values according to the training feedback of 6DOF motions of Hywind platform through comparing theDARwindsimulation results and that of experimental data. Many other dynamic responses that cannot be measured in basin experiment could be predicted in higher accuracy with this intelligentDARwind. Finally, the case study of SADA method was conducted and the results demonstrated that the mean values of the platform's motions can be predicted by AI-basedDARwindwith higher accuracy, for example the maximum error of surge motion is reduced by 21%. This proposed SADA method takes advantage of numerical-experimental method and the machine learning method, which brings a new and promising solution for overcoming the handicap impeding direct use of traditional basin experimental technology in FOWTs design.

Ti-6Al-4V alloy is used extensively in aerospace industries due to its excellent properties. In this paper, the hot die forging process of the Ti-6Al-4V alloy blade was simulated by using 3D finite element method. Based on the model, the effect of process parameters on the deformation was investigated. The results show that the increase of temperature is beneficial to improving the uniformity of stress distribution. The slower the declining velocity of upper die is, the larger the strain gradient of severe deformation area will be. In addition, the stress distribution gets uniform with velocity decreasing. The large friction coefficient can make strain distribution uneven and cause symmetry of stress distribution. The proposed numerical simulation of hot die forging of blade in the present work may yield important information for the development of hot die forging techniques and the manufacture of blade.

To investigate using pre-germinated brown rice (PGBR) to treat metabolic syndrome, we fed one group of mice standard-regular-diet (SRD) for 20 weeks and another group of mice high-fat-diet (HFD) for 16 weeks. We subdivided them into HFD group and HFD + PGBR group whose dietary carbohydrate was replaced with PGBR for 4 weeks. The HFD group gained more weight, had higher blood pressure, heart rate, blood glucose and lipids, liver levels of TG, feces TG and bile acid, lower adipose levels of adipocytokine, lower skeletal muscle IR, IRS-1, IRS-2, PI3 K, Akt/PKB, GLUT-1, GLUT-4, GCK and PPAR-γ; higher liver SREBP-1, SCD-1, FAS, HMGCR, LDLR, CYP7α1 and PPAR-α, and higher adipose SREBP-1, SCD-1, FAS, and lower adipose PPAR-α and adiponectin. The HFD + PGBR group had clearly improved blood pressure, biochemical parameters and above proteins expressions. PGBR successful treatment of metabolic syndrome was achieved through improvements in glucose and lipid synthesis and metabolism.