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We present a novel approach to estimate the value of primordial non-Gaussianity (f NL) parameter directly from the cosmic microwave background (CMB) maps using a convolutional neural network (CNN). While traditional methods rely on complex statistical techniques, this study proposes a simpler approach that employs a neural network to estimate f NL. The neural network model is trained on simulated CMB maps with known f NL in range of [−50, 50], and its performance is evaluated using various metrics. The results indicate that the proposed approach can accurately estimate f NL values from CMB maps with a significant reduction in complexity compared to traditional methods. With 500 validation data, the |$f^{\rm output}_{\rm NL}$| against |$f^{\rm input}_{\rm NL}$| graph can be fitted as y  = ax + b , where |$a=0.980^{+0.098}_{-0.102}$| and |$b=0.277^{+0.098}_{-0.101}$|⁠ , indicating the unbiasedness of the primordial non-Gaussianity estimation. The results suggest that the CNN technique can be widely applied to other cosmological parameter estimation directly from CMB images. [ABSTRACT FROM AUTHOR]

The present study describes the isolation, identification, and quantification of biomarker compounds in plant extracts of Habenaria intermedia D. Don (Orchidaceae). The isolation of the compounds was carried out from H. intermedia D. Don by repeated column chromatography of petroleum ether and ethanol fractions of extract of tubers. These compounds were characterized by 1 H and 13 C NMR and mass spectral data. A new quantitative method was established by using high-performance liquid chromatography (HPLC)-PDA. As a result, seven compounds were isolated and characterized. This is the first report of isolation of these compounds from this plant species H. intermedia D.Don. Out of seven isolated compounds, five were used for the quantitative study. A reliable and suitable HPLC method was developed for the well-resolved chromatogram of compounds. The proposed method was applied successfully to the detection and quantification of compounds. This study also represents the immunomodulatory and anti-inflammasome biological studies of isolated natural products. Loroglossol ( HBR-4 ) has been reported to possess immunomodulatory activity. The immunostimulating assay indicated that HBR-4 could significantly promote the cell proliferation, especially via IL-2, TNF-α, and IFN-γ secretion from spleen cells. These results suggested the potential utilization of HBR-4 as an attractive functional health supplement candidate for hypoimmunity population. Additionally, cyclophosphamide-induced immunosuppression was counteracted by treatment with HBR-4 , revealing significant increase in hemagglutinating antibody responses and hemolytic antibody responses. The current work revealed the potential anti-inflammasome and immunomodulatory activities of H. intermedia D. Don compounds and validates the usage of this prominent Rasayna plant., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)

Plasmon polaritons in topological insulators attract attention from a fundamental perspective and for potential THz photonic applications. Although polaritons have been observed by THz far-field spectroscopy on topological insulator microstructures, real-space imaging of propagating THz polaritons has been elusive so far. Here, we show spectroscopic THz near-field images of thin Bi 2 Se 3 layers (prototypical topological insulators) revealing polaritons with up to 12 times increased momenta as compared to photons of the same energy and decay times of about 0.48 ps, yet short propagation lengths. From the images we determine and analyze the polariton dispersion, showing that the polaritons can be explained by the coupling of THz radiation to various combinations of Dirac and massive carriers at the Bi 2 Se 3 surfaces, massive bulk carriers and optical phonons. Our work provides critical insights into the nature of THz polaritons in topological insulators and establishes instrumentation and methodology for imaging of THz polaritons., (© 2022. The Author(s).)

Background: Datura stramonium L. is widely used across the world for its therapeutic potential to treat inflammatory disorders. The current work was designed to isolate and identify steroidal lactones from D. stramonium leaves and evaluate their anti-inflammatory and analgesic properties., Methods: Several compounds were isolated from D. stramonium leaves and characterized by nuclear magnetic resonance and high-resonance electron spray ionization mass spectrometry techniques. Further, anti-inflammatory properties of these compounds were evaluated by in vitro assays, such as release of NO and pro-inflammatory cytokines by lipopolysaccharide (LPS)-activated J774A.1 macrophages. Using in vivo models, anti-inflammatory and analgesic effects were examined by mouse tail-flick, carrageenan-induced inflammation in rat paw model, vascular permeability in rats, and acetic acid-induced writhing in mice. The docking studies were performed for assessing the binding efficiency of the test compounds with cyclooxygenase-1 (COX-1) and COX-2, lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1), inducible nitric oxide synthases (iNOS) and nuclear factor-κB (NF-κB)., Results: Three lactones were isolated and confirmed as daturalactone (D1), 12-deoxywithastramonolide (D23), and daturilin (D27). Further, the isolated compounds showed nitric oxide inhibition and pro-inflammatory cytokines released by LPS-activated J774A.1 macrophages. The in vivo results suggest that D1, D23 and D27 (20 mg/kg) were able to reduce the pain and inflammation in various animal models. The docking analysis showed that these three compounds actively bind with COX-1, COX-2, LOX-1, NF-κB, and iNOS, validating the anti-inflammatory effects of the lactones., Conclusion: These findings demonstrate substantial anti-inflammatory and analgesic properties of D. stramonium-derived lactones and their potential as anti-inflammatory agents to treat chronic inflammatory ailments., (Copyright © 2021. Published by Elsevier GmbH.)