HSP90 inhibitor, celastrol, arrests human monocytic leukemia cell U937 at G0/G1 in thiol-containing agents reversible way

<p>Abstract</p> <p>Background</p> <p>Because some of heat shock protein 90's (HSP90) clients are key cell cycle regulators, HSP90 inhibition can affect the cell cycle. Recently, celastrol is identified both as a novel inhibitor of HSP90 and as a potential anti-tumor agent. However, this agent's effects on the cell cycle are rarely investigated. In this study, we observed the effects of celastrol on the human monocytic leukemia cell line U937 cell cycle.</p> <p>Results</p> <p>Celastrol affected the proliferation of U937 in a dose-dependent way, arresting the cell cycle at G0/G1 with 400 nM doses and triggering cell death with doses above 1000 nM. Cell cycle arrest was accompanied by inhibition of HSP90 ATPase activity and elevation in HSP70 levels (a biochemical hallmark of HSP90 inhibition), a reduction in Cyclin D1, Cdk4 and Cdk6 levels, and a disruption of the HSP90/Cdc37/Cdk4 complex. The observed effects of celastrol on the U937 cell cycle were thiol-related, firstly because the effects could be countered by pre-loading thiol-containing agents and secondly because celastrol and thiol-containing agents could react with each other to form new compounds.</p> <p>Conclusions</p> <p>Our results disclose a novel action of celastrol-- causing cell cycle arrest at G0/G1 phase based upon thiol-related HSP90 inhibition. Our work suggests celastrol's potential in tumor and monocyte-related disease management.</p

Effect of optimized thrombus aspiration on myocardial perfusion and prognosis in acute ST-segment elevation myocardial infarction patients with primary percutaneous coronary intervention

ObjectiveTo investigate the impact of optimized thrombus aspiration on myocardial perfusion, prognosis, and safety in patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention(primary PCI).MethodsA total of 129 patients with STEMI were randomly allocated into control group (Subgroup A and B) and experimental group(Subgroup C and D). Control group received percutaneous transluminal coronary angioplasty (PTCA),thrombus aspiration and primary PCI. Experimental group received optimized thrombus aspiration and primary PCI. The number of thrombus aspiration was less than 4 times in Subgroup A and C. The number of thrombus aspiration was performed more than 4 times in Subgroups B and D. The classification of thrombi extracted, the TIMI flow grade, the incidence of no-reflow and slow flow, cTFC, TPI and CK-MB at 12 h and 24 h after stenting, ST segment resolution of ECG after stenting, NT-proBNP, LVEFat 24 h, 30 days and 180 days after stenting were compared between groups. The incidence of intraoperative and postoperative bleeding complications, stroke events and major cardiovascular events (MACE) were recorded and compared between groups.ResultsThe classification of thrombi extracted in the experimental group was higher than that in the control group. The TIMI flow grade of the experimental group was better than the control group after thrombus aspiration. After stenting, the advantage still existed, but the difference was not statistically significant. On cTFC, the experimental group was lower than the control group, but the difference was not statistically significant; After stenting the experimental group was significantly lower than the control group. The CK-MB at 12 h and 24 h of the experimental group was lower than the control group. After thrombus aspiration the incidence of no-reflow in the experimental group was significantly lower than that in the control group; after stenting the incidence of no-reflow in the experimental group was still lower than the control group, but no statistically difference. After thrombus aspiration and stenting the incidence of slow flow in the experimental group were lower than that in the control group. After stenting, NT-proBNP at 24 h was lower in the experimental group than that in the control group, However, there was no statistical difference; after stenting, The NT-proBNP in the experimental group was lower than that in the control group at 30 days and 180 days. After stenting, LVEF of the experimental group was significantly higher than the control group at 24 h and 30 days; superiority remained after 180 days but no statistical difference. There was no statistical difference between two groups for intraoperative and postoperative bleeding complications, stroke events, and MACE events. In Subgroup analysis,there was no significant difference in the classification of thrombi extracted, TIMI flow grade, cTFC, CK-MB,NT-proBNP and LVEF between group C and D, but group A was better than group B. Analysis of variance showed that the optimal number of suction was 4–5 times.ConclusionsOptimized thrombus aspiration can significantly improve myocardial perfusion and short-term and medium-term prognosis of STEMI patients after PCI, and reduce the incidence of slow flow and no-reflow. The optimal suction times were 4–5 times. Traditional aspiration method with more aspiration times is harmful to cardiac prognosis. Thrombus aspiration does not increase the incidence of stroke events and is safe.Clinical Trial Registration: identifier, ChiCTR2300073410

DF-ParPINN: parallel PINN based on velocity potential field division and single time slice focus

Modified Benney-Luke equation (mBL equation) is a three-dimensional temporal-spatial equation with complex structures, that is a high-dimensional partial differential equation (PDE), it is also a new equation of the physical ocean field, and its solution is important for studying the internal wave-wave interaction of inclined seafloor. For conventional PDE solvers such as the pseudo-spectral method, it is difficult to solve mBL equation with both accuracy and speed. Physics-informed neural network (PINN) incorporates physical prior knowledge in deep neural networks, which can solve PDE with relative accuracy and speed. However, PINN is only suitable for solving low-dimensional PDE with simple structures, and not suitable for solving high-dimensional PDE with complex structures. This is mainly because high-dimensional PDEs usually have complex structures and high-order derivatives and are likely to be high-dimensional non-convex functions, and the high-dimensional non-convex optimization problem is an NP-hard problem, resulting in the PINN easily falling into inaccurate local optimal solutions when solving high-dimensional PDEs. Therefore, we improve the PINN for the characteristics of mBL equation and propose “DF-ParPINN: parallel PINN based on velocity potential field division and single time slice focus” to solve mBL equation with large amounts of data. DF-ParPINN consists of three modules: temporal-spatial division module of overall velocity potential field, data rational selection module of multiple time slices, and parallel computation module of high-velocity fields and low-velocity fields. The experimental results show that the solution time of DF-ParPINN is no more than 0.5s, and its accuracy is much higher than that of PINN, PIRNN, cPINN, and DeepONet. Moreover, the relative error of DF-ParPINN after deep training 1000000 epochs can be reduced to less than 0.1. The validity of DF-ParPINN proves that the improved PINN also can solve high dimensional PDE with complex structures and large amounts of data quickly and accurately, which is of great significance to the deep learning of the physical ocean field

AttGAN: attention gated generative adversarial network for spatio-temporal super-resolution of ocean phenomena

This study proposes an innovative deep learning-aided approach based on generative adversarial networks named AttGAN, which is specialized for solving the spatio-temporal super-resolution problem of ocean datasets with complex waveforms and turbulent features. The proposed method can efficiently restore the desired fine high-frequency details while maintaining high efficiency. The key idea of the proposed approach is to incorporate an attention gate in the generator, which allows for emphasizing salient features for super-resolution tasks. In addition, residual convolutional blocks are used in the generator and discriminator to extract features. By establishing regression loss, physical constraints, and adversarial loss into a comprehensive loss function, a generator that exhibits high fidelity and strong generalization capabilities is trained. The proposed AttGAN is evaluated by experiments conducted on two datasets, and the experimental results validate its superiority over state-of-the-art physical constraint models in both qualitative and quantitative metrics. Moreover, the AttGAN has faster processing times than the corresponding ocean numerical models and better quality of results.Impact statemen

Media 1: Inner structure detection by optical tomography technology based on feedback of microchip Nd:YAG lasers

Originally published in Optics Express on 20 May 2013 (oe-21-10-11819

Exploration of Aging-Care Parameters to Predict Mortality of Patients Aged 80-Years and Above with Community-Acquired Pneumonia

PURPOSE: The study explores a clinical model based on aging-care parameters to predict the mortality of hospitalized patients aged 80-year and above with community-acquired pneumonia (CAP). PATIENTS AND METHODS: In this study, four hundred and thirty-five CAP patients aged 80-years and above were enrolled in the Central Hospital of Minhang District, Shanghai during 01,01,2018–31,12,2021. The clinical data were collected, including aging-care relevant factors (ALB, FRAIL, Barthel Index and age-adjusted Charlson Comorbidity Index) and other commonly used factors. The prognostic factors were screened by multivariable logistic regression analysis. Receiver operating characteristic (ROC) curves were used to predict the mortality risk. RESULTS: Univariate analysis demonstrated that several factors, including gender, platelet distribution width, NLR, ALB, CRP, pct, pre-albumin, CURB-65, low-density, lipoprotein, Barthel Index, FRAIL, leucocyte count, neutrophil count, lymphocyte count and aCCI, were associated with the prognosis of CAP. Multivariate model analyses further identified that CURB-65 (p < 0.0001, OR = 5.44, 95% CI = 3.021–10.700), FRAIL (p < 0.0001, OR = 5.441, 95% CI = 2.611–12.25) and aCCI (p = 0.003, OR = 1.551, 95% CI = 1.165–2.099) were independent risk factors, whereas ALB (p = 0.005, OR = 0.871, 95% CI = 0.788–0.957) and Barthel Index (p = 0.0007, OR = 0.958, 95% CI = 0.933–0.981) were independent protective factors. ROC curves were plotted to further predict the in-hospital mortality and revealed that combination of three parameters (Barthel Index+ FRAI +CURB-65) showed the best performance. CONCLUSION: This study showed that CURB-65, frailty and aCCI were independent risk factors influencing prognosis. In addition, ALB and Barthel Index were protective factors for in CAP patients over 80-years old. AUC was calculated and revealed that combination of three parameters (Barthel Index+ FRAI +CURB-65) showed the best performance

Bi- and trinuclear copper(I) complexes of 1,2,3-triazole-tethered NHC ligands: synthesis, structure, and catalytic properties

A series of copper complexes (3–6) stabilized by 1,2,3-triazole-tethered N-heterocyclic carbene ligands have been prepared via simple reaction of imidazolium salts with copper powder in good yields. The structures of bi- and trinuclear copper complexes were fully characterized by NMR, elemental analysis (EA), and X-ray crystallography. In particular, [Cu2(L2)2](PF6)2 (3) and [Cu2(L3)2](PF6)2 (4) were dinuclear copper complexes. Complexes [Cu3(L4)2](PF6)3 (5) and [Cu3(L5)2](PF6)3 (6) consist of a triangular Cu3 core. These structures vary depending on the imidazolium backbone and N substituents. The copper–NHC complexes tested are highly active for the Cu-catalyzed azide–alkyne cycloaddition (CuAAC) reaction in an air atmosphere at room temperature in a CH3CN solution. Complex 4 is the most efficient catalyst among these polynuclear complexes in an air atmosphere at room temperature