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Abstract The characterization of young planets (<300 Myr) is pivotal for understanding planet formation and evolution. We present the 3–5μm transmission spectrum of the 17 Myr, Jupiter-size (R∼10R_⊕) planet, HIP 67522b, observed with JWST NIRSpec/G395H. To check for spot contamination, we obtain a simultaneousg-band transit with the Southern Astrophysical Research Telescope. The spectrum exhibits absorption features 30%–50% deeper than the overall depth, far larger than expected from an equivalent mature planet, and suggests that HIP 67522b’s mass is <20M_⊕irrespective of cloud cover and stellar contamination. A Bayesian retrieval analysis returns a mass constraint of 13.8 ± 1.0M_⊕. This challenges the previous classification of HIP 67522b as a hot Jupiter and instead, positions it as a precursor to the more common sub-Neptunes. With a density of <0.10 g cm⁻³, HIP 67522 b is one of the lowest-density planets known. We find strong absorption from H₂O and CO₂(≥7σ), a modest detection of CO (3.5σ), and weak detections of H₂S and SO₂(≃2σ). Comparisons with radiative-convective equilibrium models suggest supersolar atmospheric metallicities and solar-to-subsolar C/O ratios, with photochemistry further constraining the inferred atmospheric metallicity to 3 × 10 solar due to the amplitude of the SO₂feature. These results point to the formation of HIP 67522b beyond the water snowline, where its envelope was polluted by icy pebbles and planetesimals. The planet is likely experiencing substantial mass loss (0.01–0.03M_⊕Myr⁻¹), sufficient for envelope destruction within a gigayear. This highlights the dramatic evolution occurring within the first 100 Myr of its existence. 

Abstract DNA methylation at cytosine bases of eukaryotic DNA (5-methylcytosine, 5mC) is a heritable epigenetic mark that can regulate gene expression in health and disease. Enzymes that metabolize 5mC have been well-characterized, yet the discovery of endogenously produced signaling molecules that regulate DNA methyl-modifying machinery have not been described. Herein, we report that the free radical signaling molecule nitric oxide (NO) can directly inhibit the Fe(II)/2-OG-dependent DNA demethylases ten-eleven translocation (TET) and human AlkB homolog 2 (ALKBH2). Physiologic NO concentrations reversibly inhibited TET and ALKBH2 demethylase activity by binding to the mononuclear non-heme iron atom which formed a dinitrosyliron complex (DNIC) preventing cosubstrates (2-OG and O₂) from binding. In cancer cells treated with exogenous NO, or cells endogenously synthesizing NO, there was a global increase in 5mC and 5-hydroxymethylcytosine (5hmC) in DNA, the substrates for TET, that could not be attributed to increased DNA methyltransferase activity. 5mC was also elevated in NO-producing cell-line-derived mouse xenograft and patient-derived xenograft tumors. Genome-wide DNA methylome analysis of cells chronically treated with NO (10 days) demonstrated enrichment of 5mC and 5hmC at gene-regulatory loci which correlated to changes in the expression of NO-regulated tumor-associated genes. Regulation of DNA methylation is distinctly different from canonical NO signaling and represents a novel epigenetic role for NO. 

Abstract Teeth scans are essential for many applications in orthodontics, where the teeth structures are virtualized to facilitate the design and fabrication of the prosthetic piece. Nevertheless, due to the limitations caused by factors such as viewing angles, occlusions, and sensor resolution, the 3D scanned point clouds (PCs) could be noisy or incomplete. Hence, there is a critical need to enhance the quality of the teeth PCs to ensure a suitable dental treatment. Toward this end, we propose a systematic framework including a two-step data augmentation (DA) technique to augment the limited teeth PCs and a hybrid deep learning (DL) method to complete the incomplete PCs. For the two-step DA, we first mirror and combine the PCs based on the bilateral symmetry of the human teeth and then augment the PCs based on an iterative generative adversarial network (GAN). Two filters are designed to avoid the outlier and duplicated PCs during the DA. For the hybrid DL, we first use a deep autoencoder (AE) to represent the PCs. Then, we propose a hybrid approach that selects the best completion to the teeth PCs from AE and a reinforcement learning (RL) agent-controlled GAN. Ablation study is performed to analyze each component’s contribution. We compared our method with other benchmark methods including point cloud network (PCN), cascaded refinement network (CRN), and variational relational point completion network (VRC-Net), and demonstrated that the proposed framework is suitable for completing teeth PCs with good accuracy over different scenarios. 

Abstract BackgroundMouse is probably the most important model organism to study mammal biology and human diseases. A better understanding of the mouse genome will help understand the human genome, biology and diseases. However, despite the recent progress, the characterization of the regulatory sequences in the mouse genome is still far from complete, limiting its use to understand the regulatory sequences in the human genome. ResultsHere, by integrating binding peaks in ~ 9,000 transcription factor (TF) ChIP-seq datasets that cover 79.9% of the mouse mappable genome using an efficient pipeline, we were able to partition these binding peak-covered genome regions into acis-regulatory module (CRM) candidate (CRMC) set and a non-CRMC set. The CRMCs contain 912,197 putative CRMs and 38,554,729 TF binding sites (TFBSs) islands, covering 55.5% and 24.4% of the mappable genome, respectively. The CRMCs tend to be under strong evolutionary constraints, indicating that they are likelycis-regulatory; while the non-CRMCs are largely selectively neutral, indicating that they are unlikelycis-regulatory. Based on evolutionary profiles of the genome positions, we further estimated that 63.8% and 27.4% of the mouse genome might code for CRMs and TFBSs, respectively. ConclusionsValidation using experimental data suggests that at least most of the CRMCs are authentic. Thus, this unprecedentedly comprehensive map of CRMs and TFBSs can be a good resource to guide experimental studies of regulatory genomes in mice and humans. 

Abstract Records of pressure variations on seismographs were historically considered unwanted noise; however, increased deployments of collocated seismic and acoustic instrumentation have driven recent efforts to use this effect induced by both wind and anthropogenic explosions to invert for near-surface Earth structure. These studies have been limited to shallow structure because the pressure signals have relatively short wavelengths (<∼300 m). However, the 2022 eruption of Hunga Tonga–Hunga Ha’apai (also called “Hunga”) volcano in Tonga generated rare, globally observed, high-amplitude infrasound signals with acoustic wavelengths of tens of kilometers. In this study, we examine the acoustic-to-seismic coupling generated by the Hunga eruption across 82 Global Seismographic Network (GSN) stations and show that ground motion amplitudes are related to upper (0 to ∼5 km) crust material properties. We find high (>0.8) correlations between pressure and vertical component ground motion at 83% of the stations, but only 30% of stations show this on the radial component, likely due to complex tilt effects. We use average elastic properties in the upper 5.2 km from the CRUST1.0 model to estimate vertical seismic/acoustic coupling coefficients (SV/A) across the GSN network and compare these to recorded observations. We exclude many island stations from these comparisons because the 1° resolution of the CRUST1.0 model places a water layer below these stations. Our simple modeling can predict observed SV/A within a factor of 2 for 94% of the 51 non-island GSN stations with high correlations between pressure and ground motion. These results indicate that analysis of acoustic-to-seismic coupling from the eruption could be used to place additional constraints on crustal structure models at stations with collocated seismic and pressure sensors. Ultimately, this could improve tomographic imaging models, which rely on methods that are sensitive to local structure. 

A series of BN-incorporated borafluorenate heterocycles, bis(borafluorene-phosphinimine)s (11–15), have been formed via intramolecular Staudinger-type reactions. The reactions were promoted by light or heat using monodentate phosphine-stabilized 9-azido-9-borafluorenes (R3P-BF-N3; 6–10) and involve the release of dinitrogen (N2), migration of phosphine from boron to nitrogen, and oxidation of the phosphorus center (PIII to PV). Density functional theory (DFT) calculations provide mechanistic insight into the formation of these compounds. Compounds 11–15 are blue emissive in the solution and solid states with absolute quantum yields (ΦF) ranging from 12 to 68%.