MRI Analysis of White Matter Myelin Water Content in Multiple Sclerosis: A Novel Approach Applied to Finding Correlates of Cortical Thinning

A novel lesion-mask free method based on a gamma mixture model was applied to myelin water fraction (MWF) maps to estimate the association between cortical thickness and myelin content, and how it differs between relapsing-remitting (RRMS) and secondary-progressive multiple sclerosis (SPMS) groups (135 and 23 patients, respectively). It was compared to an approach based on lesion masks. The gamma mixture distribution of whole brain, white matter (WM) MWF was characterized with three variables: the mode (most frequent value) m1 of the gamma component shown to relate to lesion, the mode m2 of the component shown to be associated with normal appearing (NA) WM, and the mixing ratio (λ) between the two distributions. The lesion-mask approach relied on the mean MWF within lesion and within NAWM. A multivariate regression analysis was carried out to find the best predictors of cortical thickness for each group and for each approach. The gamma-mixture method was shown to outperform the lesion-mask approach in terms of adjusted R2, both for the RRMS and SPMS groups. The predictors of the final gamma-mixture models were found to be m1 (β = 1.56, p \u3c 0.005), λ (β = −0.30, p \u3c 0.0005) and age (β = −0.0031, p \u3c 0.005) for the RRMS group (adjusted R2 = 0.16), and m2 (β = 4.72, p \u3c 0.0005) for the SPMS group (adjusted R2 = 0.45). Further, a DICE coefficient analysis demonstrated that the lesion mask had more overlap to an ROI associated with m1, than to an ROI associated with m2 (p \u3c 0.00001), and vice versa for the NAWM mask (p \u3c 0.00001). These results suggest that during the relapsing phase, focal WM damage is associated with cortical thinning, yet in SPMS patients, global WM deterioration has a much stronger influence on secondary degeneration. Through these findings, we demonstrate the potential contribution of myelin loss on neuronal degeneration at different disease stages and the usefulness of our statistical reduction technique which is not affected by the typical bias associated with approaches based on lesion masks

Use of a mixed tissue RNA design for performance assessments on multiple microarray formats

The comparability and reliability of data generated using microarray technology would be enhanced by use of a common set of standards that allow accuracy, reproducibility and dynamic range assessments on multiple formats. We designed and tested a complex biological reagent for performance measurements on three commercial oligonucleotide array formats that differ in probe design and signal measurement methodology. The reagent is a set of two mixtures with different proportions of RNA for each of four rat tissues (brain, liver, kidney and testes). The design provides four known ratio measurements of >200 reference probes, which were chosen for their tissue-selectivity, dynamic range coverage and alignment to the same exemplar transcript sequence across all three platforms. The data generated from testing three biological replicates of the reagent at eight laboratories on three array formats provides a benchmark set for both laboratory and data processing performance assessments. Close agreement with target ratios adjusted for sample complexity was achieved on all platforms and low variance was observed among platforms, replicates and sites. The mixed tissue design produces a reagent with known gene expression changes within a complex sample and can serve as a paradigm for performance standards for microarrays that target other species

DUALZ: Deep UNCOVER-ALMA Legacy High-Z Survey

We present the survey design and initial results of the ALMA Cycle 9 program of DUALZ, which aims to establish a joint ALMA and JWST public legacy field targeting the massive galaxy cluster Abell 2744. DUALZ features a contiguous $4'\times6'$ ALMA 30-GHz-wide mosaic in Band 6, covering areas of $\mu>2$ down to a sensitivity of $\sigma=32.7~\mu$Jy. Through a blind search, we identified 69 dust continuum sources at S/N $\gtrsim5.0$ with median redshift and intrinsic 1.2-mm flux of $z=2.30$ and $S_{\rm 1.2mm}^{\rm int}=0.24$~mJy. Of these, 27 have been spectroscopically confirmed, leveraged by the latest NIRSpec observations, while photometric redshift estimates are constrained by the comprehensive HST, NIRCam, and ALMA data for the remaining sources. With priors, we further identify a [CII]158 $\mu$m line emitter at $z=6.3254\pm0.0004$, confirmed by the latest NIRSpec spectroscopy. The NIRCam counterparts of the 1.2-mm continuum exhibit undisturbed morphologies, denoted either by disk or spheroid, implying the triggers for the faint mm emission are less catastrophic than mergers. We have identified 8 HST-dark galaxies (F150W$>$27mag, F150W$-$F444W$>$2.3) and 2 JWST-dark (F444W$>$30mag) galaxy candidates among the ALMA continuum sources. The former includes face-on disk galaxies, hinting that substantial dust obscuration does not always result from inclination. We also detect a marginal dust emission from an X-ray-detected galaxy at $z_{\rm spec}=10.07$, suggesting an active co-evolution of the central black hole and its host. We assess the infrared luminosity function up to $z\sim10$ and find it consistent with predictions from galaxy formation models. To foster diverse scientific outcomes from the community, we publicly release reduced ALMA mosaic maps, cubes, and the source catalog.Comment: 33 pages, 16 figures, and 5 tables. Submitted to ApJS. The ALMA products are fully available from here: https://jwst-uncover.github.io/DR2.html#DUAL

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

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

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

The JWST UNCOVER Treasury survey: Ultradeep NIRSpec and NIRCam ObserVations before the Epoch of Reionization

In this paper we describe the survey design for the Ultradeep NIRSpec and NIRCam ObserVations before the Epoch of Reionization (UNCOVER) Cycle 1 JWST Treasury program, which executed its early imaging component in November 2022. The UNCOVER survey includes ultradeep ($\sim29-30\mathrm{AB}$) imaging of $\sim$45 arcmin$^2$ on and around the well-studied Abell 2744 galaxy cluster at $z=0.308$ and will follow-up ${\sim}500$ galaxies with extremely deep low-resolution spectroscopy with the NIRSpec/PRISM during the summer of 2023. We describe the science goals, survey design, target selection, and planned data releases. We also present and characterize the depths of the first NIRCam imaging mosaic, highlighting previously unparalleled resolved and ultradeep 2-4 micron imaging of known objects in the field. The UNCOVER primary NIRCam mosaic spans 28.8 arcmin$^2$ in seven filters (F115W, F150W, F200W, F277W, F356W, F410M, F444W) and 16.8 arcmin$^2$ in our NIRISS parallel (F115W, F150W, F200W, F356W, and F444W). To maximize early community use of the Treasury data set, we publicly release full reduced mosaics of public JWST imaging including 45 arcmin$^2$ NIRCam and 17 arcmin$^2$ NIRISS mosaics on and around the Abell 2744 cluster, including the Hubble Frontier Field primary and parallel footprints.Comment: 17 pages, 8 figures, 4 tables, submitted to ApJ, comments welcome (v2 with full author list in metadata

The Immunophilin-Like Protein XAP2 Is a Negative Regulator of Estrogen Signaling through Interaction with Estrogen Receptor α

XAP2 (also known as aryl hydrocarbon receptor interacting protein, AIP) is originally identified as a negative regulator of the hepatitis B virus X-associated protein. Recent studies have expanded the range of XAP2 client proteins to include the nuclear receptor family of transcription factors. In this study, we show that XAP2 is recruited to the promoter of ERα regulated genes like the breast cancer marker gene pS2 or GREB1 and negatively regulate the expression of these genes in MCF-7 cells. Interestingly, we show that XAP2 downregulates the E2-dependent transcriptional activation in an estrogen receptor (ER) isoform-specific manner: XAP2 inhibits ERα but not ERβ-mediated transcription. Thus, knockdown of intracellular XAP2 levels leads to increased ERα activity. XAP2 proteins, carrying mutations in their primary structures, loose the ability of interacting with ERα and can no longer regulate ER target gene transcription. Taken together, this study shows that XAP2 exerts a negative effect on ERα transcriptional activity and may thus prevent ERα-dependent events

JWST reveals a possible z∼11z \sim 11 galaxy merger in triply-lensed MACS0647−-JD

MACS0647$-$JD is a triply-lensed $z\sim11$ galaxy originally discovered with the Hubble Space Telescope. Here we report new JWST imaging, which clearly resolves MACS0647$-$JD as having two components that are either merging galaxies or stellar complexes within a single galaxy. Both are very small, with stellar masses $\sim10^8\,M_\odot$ and radii $r<100\,\rm pc$. The brighter larger component "A" is intrinsically very blue ($\beta\sim-2.6$), likely due to very recent star formation and no dust, and is spatially extended with an effective radius $\sim70\,\rm pc$. The smaller component "B" appears redder ($\beta\sim-2$), likely because it is older ($100-200\,\rm Myr$) with mild dust extinction ($A_V\sim0.1\,\rm mag$), and a smaller radius $\sim20\,\rm pc$. We identify galaxies with similar colors in a high-redshift simulation, finding their star formation histories to be out of phase. With an estimated stellar mass ratio of roughly 2:1 and physical projected separation $\sim400\,\rm pc$, we may be witnessing a galaxy merger 400 million years after the Big Bang. We also identify a candidate companion galaxy C $\sim3\,{\rm kpc}$ away, likely destined to merge with galaxies A and B. The combined light from galaxies A+B is magnified by factors of $\sim$8, 5, and 2 in three lensed images JD1, 2, and 3 with F356W fluxes $\sim322$, $203$, $86\,\rm nJy$ (AB mag 25.1, 25.6, 26.6). MACS0647$-$JD is significantly brighter than other galaxies recently discovered at similar redshifts with JWST. Without magnification, it would have AB mag 27.3 ($M_{UV}=-20.4$). With a high confidence level, we obtain a photometric redshift of $z=10.6\pm0.3$ based on photometry measured in 6 NIRCam filters spanning $1-5\rm\mu m$, out to $4300\,\r{A}$ rest-frame. JWST NIRSpec observations planned for January 2023 will deliver a spectroscopic redshift and a more detailed study of the physical properties of MACS0647$-$JD.Comment: 27 pages, 14 figures, submitted to Natur