Different Strategies for the Treatment of Age-Related Macular Degeneration in China: An Economic Evaluation

Purpose. To assess the cost-effectiveness of bevacizumab compared to ranibizumab, verteporfin photodynamic therapy (PDT), and usual care for the treatment of age-related macular degeneration (AMD) in China. Methods. A Markov model was developed according to patient visual acuity (VA) in the better-seeing eye (Snellen scale). Four cohorts of patients were treated with one of the following therapies: bevacizumab, ranibizumab, PDT, or usual care. Clinical data related to treatments were obtained from published randomized clinical trials. Direct medical costs and resource utilization in the Chinese health care setting were taken into account. Health and economic outcomes were evaluated over a lifetime horizon. Sensitivity analyses were performed. Results. Treatment with ranibizumab provided the greatest gains in quality-adjusted life-years (QALYs). The cost per marginal QALY gained with bevacizumab over usual care was $1,258,$3,803, and $2,066 for the predominantly classic, minimally classic, and occult lesions, respectively. One-way sensitivity analysis showed considerably influential factors, such as utility values and effectiveness data. Probabilistic sensitivity analysis indicated that, compared to usual care, PDT and ranibizumab most cases would be cost-effective in the bevacizumab arm at a threshold of$7,480/QALY. Conclusion. Bevacizumab can be a cost-effective option for the treatment of AMD in the Chinese setting

Research on Innovation Ecosystem of the Crowd Innovation Space Based on System Dynamics

The crowd innovation space is a new innovation business service platform, developed from the traditional incubator, including makerspace, entrepreneurship café and so on. It is essential for mass entrepreneurship and innovation to get full use of the creativity of the crowed innovation space and explore new impetus in New Economic Norm. Based on the traditional enterprise innovation ecosystem theory, this paper explores the connotation of innovation ecosystem of the crowd innovation space. And then, we use the knowledge to model the innovation ecosystem of the crowd innovation space with system dynamics. Based on the model, we explore the operational mechanism of innovation ecosystem of the crowd innovation space. Through the analysis of the operational mechanism and connotation, we put forward to some proposal to improve the effectiveness of the service ability in innovation of the crowd innovation space

In vivo and in silico investigation of selected herbal compounds as anti-tubercular agents

Purpose: To investigate whether some herbal compounds, namely, arctiin, NSC333050, cnicin, and arctigenin, can be used as anti-tubercular agents using in vivo and in silico techniques.Methods: A set of structurally diverse herbal compounds were screened for anti-tubercular activity against the Mycobacterium tuberculosis (Mtb) H37v strain by determining their microbial inhibitory concentration (MIC) and cytotoxicity. The compounds were also screened using in silico techniques, such as molecular docking and absorption, distribution, metabolism, and excretion (ADME) prediction.Results: The in vivo methods, such as determination of MIC and cytotoxicity assay, revealed that some of the herbal compounds showed superior anti-tubercular activity. In silico approaches involving molecular docking simulations for the mycobacterial enzymes Mtb DNA gyrase, Mtb betalactamase, Mtb diaminopelargonic acid synthase, and Mtb cytidine 5'-triphosphate synthase (CTP) confirmed that the inhibitory activities of the herbal compounds occurred at the active sites of these enzyme. In silico ADME prediction also confirmed the pharmacokinetic safety of these herbal compounds.Conclusion: Arctiin, NSC333050, cnicin, and arctigenin, are suitable candidates for clinical evaluation for the treatment of respiratory infections caused by Mtb.Keywords: Tuberculosis, Microbial inhibitory concentration, Arctiin, Cnicin, Arctigenin, In silico, Respiratory infectio

Asymptotic-Preserving Convolutional DeepONets Capture the Diffusive Behavior of the Multiscale Linear Transport Equations

In this paper, we introduce two types of novel Asymptotic-Preserving Convolutional Deep Operator Networks (APCONs) designed to address the multiscale time-dependent linear transport problem. We observe that the vanilla physics-informed DeepONets with modified MLP may exhibit instability in maintaining the desired limiting macroscopic behavior. Therefore, this necessitates the utilization of an asymptotic-preserving loss function. Drawing inspiration from the heat kernel in the diffusion equation, we propose a new architecture called Convolutional Deep Operator Networks, which employ multiple local convolution operations instead of a global heat kernel, along with pooling and activation operations in each filter layer. Our APCON methods possess a parameter count that is independent of the grid size and are capable of capturing the diffusive behavior of the linear transport problem. Finally, we validate the effectiveness of our methods through several numerical examples

Flemingia macrophylla Extract Ameliorates Experimental Osteoporosis in Ovariectomized Rats

Flemingia macrophylla (Leguminosae), a native plant of Taiwan, is used as folk medicine. An in vitro study showed that a 75% ethanolic extract of F. macrophylla (FME) inhibited osteoclast differentiation of cultured rat bone marrow cells, and the active component, lespedezaflavanone A (LDF-A), was isolated. It was found that oral administration of FME for 13 weeks suppressed bone loss in ovariectomized rats, an experimental model of osteoporosis. In addition, FME decreased urinary deoxypyridinoline concentrations but did not inhibit serum alkaline phosphatase activities, indicating that it ameliorated bone loss via inhibition of bone resorption. These results suggest that FME may represent a useful remedy for the treatment of bone resorption diseases, such as osteoporosis. In addition, LDF-A could be used as a marker compound to control the quality of FME

Revisiting Puffy Dark Matter with Novel Insights: Partial Wave Analysis

We present a comprehensive study on the self-interaction cross-section of puffy dark matter (DM) particles, which have a significant intrinsic size compared to their Compton wavelength. For such puffy DM self-interaction cross-section in the resonant and classical regimes, our study demonstrates the significance of the Yukawa potential and the necessity of partial wave analysis: (i) Due to the finite-size effect of puffy DM particles, the new Yukawa potential of puffy DM is found to enlarge the Born-effective regime for the self-interaction cross-section, compared with the point-like DM; (ii) Our partial wave analysis shows that depending on the value of the ratio between $R_{\chi}$ (radius of a puffy DM particle) and $1/m_{\phi}$ (force range), the three regimes (Born-effective, resonant and classical) for puffy DM self-interaction cross-section can be very different from the point-like DM; (iii) We find that to solve the small-scale anomalies via self-interacting puffy DM, the Born-effective and the resonant regimes exist for dwarf galaxies, while for the cluster and Milky Way galaxy the non-Born regime is necessary.Comment: 17 pages, 8 figures, accepted by JHE