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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]

Perinatal nicotine exposure via tobacco smoking results in increased proclivity to chronic lung disease (CLD); however, the underlying molecular mechanisms remain incompletely understood. We previously demonstrated that in addition to nicotine's direct effects on the developing lung, there are also adverse molecular alterations in bone marrow-derived mesenchymal stem cells (BMSCs), which are vital to lung injury repair. Whether perinatal nicotine exposure via electronic-cigarette (e-cig) vaping also adversely affects BMSCs is unknown. This is highly relevant due to marked increase in e-cig vaping including by pregnant women. Hypothesizing that perinatal nicotine exposure via e-cig vaping predisposes BMSCs to a pro-myofibroblastic phenotype, pregnant rat dams were exposed to fresh air (control), vehicle (e-cig without nicotine), or e-cig (e-cig with nicotine) daily during pregnancy and lactation. At postnatal day 21, offspring BMSCs were isolated and studied for cell proliferation, migration, wound healing response, and expression of key Wnt and PPARγ signaling intermediates (β-catenin, LEF-1, PPARγ, ADRP and C/EBPα) and myogenic markers (fibronectin, αSMA, calponin) proteins using immunoblotting. Compared to controls, perinatal e-cig exposure resulted in significant decrease in BMSC proliferation, migration, and wound healing response. The expression of key Wnt signaling intermediates (β-catenin, LEF-1) and myogenic markers (fibronectin, αSMA, calponin) increased significantly, while PPARγ signaling intermediates (PPARγ, ADRP, and C/EBPα) decreased significantly. Based on these data, we conclude that perinatally e-cig exposed BMSCs demonstrate pro-myofibroblastic phenotype and impaired injury-repair potential, indicating a potentially similar susceptibility to CLD following perinatal nicotine exposure via vaping as seen following parenteral perinatal nicotine exposure., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)