Probing the Structure of Kepler ZZ Ceti Stars with Full Evolutionary Models-based Asteroseismology

We present an asteroseismological analysis of four ZZ Ceti stars observed with the Kepler spacecraft: GD 1212, SDSS J113655.17+040952.6, KIC 11911480, and KIC 4552982, based on a grid of full evolutionary models of DA white dwarf (WD) stars. We employ a grid of carbon–oxygen core models, characterized by a detailed and consistent chemical inner profile for the core and the envelope. In addition to the observed periods, we take into account other information from the observational data, such as amplitudes, rotational splittings, and period spacing, as well as photometry and spectroscopy. For each star, we present an asteroseismological model that closely reproduces their observed properties. The asteroseismological stellar mass and effective temperature of the target stars are (0.632 0.027 ± M☉, 10737 ± 73 K) for GD 1212, (0.745 0.007 ± M☉, 11110 ± 69 K) for KIC 4552982, (0.5480 0.01 ± M☉, 12,721 ± 228 K) for KIC11911480, and (0.570 0.01 ± M☉, 12,060 ± 300 K) for SDSS J113655.17+040952.6. In general, the asteroseismological values are in good agreement with the spectroscopy. For KIC 11911480 and SDSS J113655.17+040952.6 we derive a similar seismological mass, but the hydrogen envelope is an order of magnitude thinner for SDSS J113655.17+040952.6, which is part of a binary system and went through a common envelope phase

Ultrasound-evoked immediate early gene expression in the brainstem of the Chinese torrent frog, Odorrana tormota

The concave-eared torrent frog, Odorrana tormota, has evolved the extraordinary ability to communicate ultrasonically (i.e., using frequencies > 20 kHz), and electrophysiological experiments have demonstrated that neurons in the frog’s midbrain (torus semicircularis) respond to frequencies up to 34 kHz. However, at this time, it is unclear which region(s) of the torus and what other brainstem nuclei are involved in the detection of ultrasound. To gain insight into the anatomical substrate of ultrasound detection, we mapped expression of the activity-dependent gene, egr-1, in the brain in response to a full-spectrum mating call, a filtered, ultrasound-only call, and no sound. We found that the ultrasound-only call elicited egr-1 expression in the superior olivary and principal nucleus of the torus semicircularis. In sampled areas of the principal nucleus, the ultrasound-only call tended to evoke higher egr-1 expression than the full-spectrum call and, in the center of the nucleus, induced significantly higher egr-1 levels than the no-sound control. In the superior olivary nucleus, the full-spectrum and ultrasound-only calls evoked similar levels of expression that were significantly greater than the control, and egr-1 induction in the laminar nucleus showed no evidence of acoustic modulation. These data suggest that the sampled areas of the principal nucleus are among the regions sensitive to ultrasound in this species

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies