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Unveiling shifts in Eurasian annual temperature cycles under anthropogenic warming

Latent heat-assisted cooling for high-efficiency solar-driven freshwater production

Evaluation and analysis of delamination on drilled holes of industrial waste based novel agave sisalana/glass fiber reinforced hybrid composites

Diminished osteoprotegerin production by gingival fibroblasts from periodontitis patients is associated with their reduced ability to suppress osteoclastogenesis

Abstract Osteoclast-mediated alveolar bone resorption is a key hallmark of periodontitis. Gingival fibroblasts (GFs) play multifaceted roles in the progression of chronic inflammation; however, their involvement in osteoclastogenesis remains controversial. Here, we analyzed the effects of mediators secreted by GFs from healthy donors and periodontitis patients on osteoclast formation. We observed strong suppression of receptor activator of nuclear factor kappa-B ligand (RANKL)-induced osteoclastogenesis by conditioned media from healthy donor GFs, which was independent of any prior in vitro stimulation or infection. These media contained high levels of osteoprotegerin (OPG), and GFs were identified as the main OPG source in gingival tissue using a 3D organotypic reconstructed human gingiva model and a single-cell RNA-seq dataset. Notably, GFs from periodontitis patients produced significantly less OPG compared to GFs from healthy individuals and were less effective at suppressing osteoclastogenesis. Finally, siRNA-mediated silencing of OPG expression in GFs from periodontitis patients further decreased their inhibitory effect on osteoclast formation, confirming the central role of OPG in osteoclastogenesis regulation by GFs. Collectively, these results demonstrate that in healthy gingival tissue, GFs exert bone-protective effects by inhibiting osteoclast formation. However, prolonged exposure to the microenvironment of the inflamed gingival tissue could impair this protective function through sustained reduction of OPG production, which may contribute to alveolar bone resorption in periodontitis.

The alkenes Z9-C29 and Z9-C31 function as quorum-sensing pheromones stimulating worker reproduction in the bumble bee Bombus terrestris

Discriminability of selected periods III‒IV elements in photon-counting computed tomography using a pixelated CdTe detector

Abstract This study introduces a new approach in photon-counting computed tomography (CT) for elemental discrimination in periods III and IV of the periodic table of elements, which have not been covered by conventional methods that rely on the K-absorption edge of the target element. The present method features a pixelated CdTe detector with positional sensitivity and energy resolution. The authors changed its energy threshold level to determine the worthiness of counting an energy deposition by an X-ray photon in a pixel rather than changing the tube voltage in accordance with the target element as in the conventional method. The differences between the images are visualised on a scatter plot against various threshold levels, which clearly separates iron (atomic number 26) and copper (atomic number 29) with minimal overlap after normalising the CT values of aluminium and air to 0 and −1000, respectively. The discriminability was quantified using the Bhattacharyya coefficient. This elemental discrimination method does not rely on the K-absorption edge of the target element and can therefore be broadly applied to other elements in non-destructive (non-invasive) industrial and biomedical CT inspections.

Chaotic analysis, hopf bifurcation and collision of optical periodic solitons in (2+1)-dimensional degenerated Biswas–Milovic equation with Kerr law of nonlinearity

Dominant substitutions underlying the antigenic evolution of H5 influenza virus

RING1B-BMI1 catalyzed dynamic H2AK119ub1 modification in response to sonic hedgehog signalling during pancreatic differentiation of human embryonic stem cells

Abstract Human embryonic stem cells (ESCs) can differentiate into the pancreatic lineage and thus can serve as in vitro models for normal pancreas development. Epigenetic modulators such as RING1B and BMI1, are essential lineage regulators of the pancreatic lineage. Inhibition of the sonic hedgehog (SHH) pathway is critical for development of the pancreatic lineage. In several cancers, SHH signals regulate BMI1 protein. However, it is unclear whether SHH pathway can direct RING1B and BMI1 to the promoters of pancreas-specific genes during human pancreas development to regulate them. We performed chromatin immunoprecipitation coupled with qPCR to assess if RING1B and BMI1 occupy pancreas gene promoters and repress them by adding the repressive H2AK119ub1 mark. We compared the RING1B – BMI1 occupancy at 1000 bp upstream of the pancreas specific gene promoters across cells treated with exogenous sonic hedgehog as well as the pathway inhibitor– SANT1. We observed that the SHH pathway alters the expression of crucial pancreas genes as well as regulates RING1B and BMI1 occupancy at these gene promoters. PcG protein occupancy correlated with expression of HNF4α and HHEX; but surprisingly did not affect the mRNA expression of the master transcription factor, PDX1 . Ou results demonstrate that during pancreatic differentiation from human embryonic stem cells, the SHH signalling pathway affects occupancy of PcG proteins – RING1B and BMI1.

Regime-adaptive partial differential equations for interpretable multi-ethnic urban modeling

Argonaute-HNH filaments triggered by invader DNA confer bacterial immunity

Experimental study on the performance and mechanism of high-pressure abrasive water jet cutting GFRP bars reinforced concrete structures

Estimating PM2.5 concentrations at public schools in North Carolina using multiple data sources and interpolation methods

SINDy-RL for interpretable and efficient model-based reinforcement learning

Abstract Deep reinforcement learning (DRL) has shown significant promise for uncovering sophisticated control policies that interact in complex environments, such as stabilizing a tokamak fusion reactor or minimizing the drag force on an object in a fluid flow. However, DRL requires an abundance of training examples and may become prohibitively expensive for many applications. In addition, the reliance on deep neural networks often results in an uninterpretable, black-box policy that may be too computationally expensive to use with certain embedded systems. Recent advances in sparse dictionary learning, such as the sparse identification of nonlinear dynamics (SINDy), have shown promise for creating efficient and interpretable data-driven models in the low-data regime. In this work, we introduce SINDy-RL, a unifying framework for combining SINDy and DRL to create efficient, interpretable, and trustworthy representations of the dynamics model, reward function, and control policy. We demonstrate the effectiveness of our approaches on benchmark control environments and flow control problems, including gust mitigation on a 3D NACA 0012 airfoil at R e  = 1000. SINDy-RL achieves comparable performance to modern DRL algorithms using significantly fewer interactions in the environment and results in an interpretable control policy orders of magnitude smaller than a DRL policy.

Dry sliding wear behavior of SiC-reinforced Al-Si eutectic metal matrix composite

Abstract This study investigates the effect of sliding parameters on the dry sliding wear behavior of (silicon carbide) SiC-reinforced (aluminum silicon) Al-Si eutectic metal matrix composites (MMCs) with 1.5 wt% of magnesium (Mg). The composites were fabricated by incorporating varying amounts of SiC particles into the aluminum-silicon matrix to improve wear resistance. A comprehensive wear analysis was conducted under different sliding speeds, normal loads, sliding distances, and SiC reinforcement contents. The Taguchi method was used to optimize the wear performance, with signal-to-noise (SN) ratios employed to assess the influence of each sliding parameter. The findings show that wear rate is mainly influenced by SiC content (32.04%), normal load (30.98%), and sliding speed (10.99%), while the coefficient of friction (COF) is largely affected by normal load (38.51%), SiC content (34.46%), and sliding distance (23.51%). The study also reveals that the addition of SiC reinforcement improves the wear resistance of the developed composite. The findings suggest that optimizing these parameters can significantly reduce wear, making these composites suitable for advanced engineering applications where high wear resistance is critical.

Engineering attributes of coir fibre ash incorporated sustainable lime concrete

Dual transition metal electrocatalysis for difluoromethylation of Aryl halides using potassium difluoroacetate

Safety and efficacy of niosomal and conventional tranexamic acid/niacinamide vs. hydroquinone creams in melasma: A randomized, double-blind, case-controlled clinical trial

Effect of mineral materials heterogeneity on rock failure: insights from a uniaxial compressive test of sandstone by in-situ x-ray computed tomography

Electronic energy levels and optical spectra of trivalent lanthanide ions in water – Ce(III), Pr(III), Nd(III), Sm(III), Eu(III), Gd(III), Tb(III), Dy(III), Ho(III), Er(III), Tm(III), and Yb(III)