The Near-Infrared Imager and Slitless Spectrograph (NIRISS) is the science module of the Canadian-built Fine Guidance Sensor (FGS) onboard the James Webb Space Telescope (JWST). NIRISS has four ...observing modes: 1) broadband imaging featuring seven of the eight NIRCam broadband filters, 2) wide-field slitless spectroscopy (WFSS) at a resolving power of \(\sim\)150 between 0.8 and 2.2 \(\mu\)m, 3) single-object cross-dispersed slitless spectroscopy (SOSS) enabling simultaneous wavelength coverage between 0.6 and 2.8 \(\mu\)m at R\(\sim\)700, a mode optimized for exoplanet spectroscopy of relatively bright (\(J<6.3\)) stars and 4) aperture masking interferometry (AMI) between 2.8 and 4.8 \(\mu\)m enabling high-contrast (\(\sim10^{-3}-10^{-4}\)) imaging at angular separations between 70 and 400 milliarcsec for relatively bright (\(M<8\)) sources. This paper presents an overview of the NIRISS instrument, its design, its scientific capabilities, and a summary of in-flight performance. NIRISS shows significantly better response shortward of \(\sim2.5\,\mu\)m resulting in 10-40% sensitivity improvement for broadband and low-resolution spectroscopy compared to pre-flight predictions. Two time-series observations performed during instrument commissioning in the SOSS mode yield very stable spectro-photometry performance within \(\sim\)10% of the expected noise. The first space-based companion detection of the tight binary star AB Dor AC through AMI was demonstrated.
Age-related macular degeneration (AMD) is the leading cause of acquired and irreversible blindness among elderly Americans. Most AMD patients have the dry form of the disease (dAMD) for which ...reliable therapies are lacking. A major obstacle to the development of effective treatments is a deficit in our understanding of what triggers dAMD onset. This is particularly the case with respect to the events that cause retinal pigment epithelial (RPE) cells to transition from a state of health and homeostasis to one of dysfunction and atrophy. These cells provide critical support to the photoreceptors and their atrophy often precipitates photoreceptor death in dAMD. Chronic oxidative stress is a primary driver of age-dependent, RPE atrophy. Sources of this stress have been identified (e.g., cigarette smoke, photooxidized bisretinoids), but we still do not understand how these stressors damage RPE constituents or what age-dependent changes undermine the cytoprotective systems in the RPE. This review focuses on Nrf2, the master antioxidant transcription factor, and its role in the RPE during aging and dAMD onset.
Abstract
Cells within the tumour microenvironment (TME) can impact tumour development and influence treatment response. Computational approaches have been developed to deconvolve the TME from bulk ...RNA-seq. Using scRNA-seq profiling from breast tumours we simulate thousands of bulk mixtures, representing tumour purities and cell lineages, to compare the performance of nine TME deconvolution methods (BayesPrism, Scaden, CIBERSORTx, MuSiC, DWLS, hspe, CPM, Bisque, and EPIC).
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ome methods are more robust in deconvolving mixtures with high tumour purity levels. Most methods tend to mis-predict normal epithelial for cancer epithelial as tumour purity increases, a finding that is validated in two independent datasets. The breast cancer molecular subtype influences this mis-prediction. BayesPrism and DWLS have the lowest combined numbers of false positives and false negatives, and have the best performance when deconvolving granular immune lineages. Our findings highlight the need for more single-cell characterisation of rarer cell types, and suggest that tumour cell compositions should be considered when deconvolving the TME.
Uncertainty estimation is crucial for understanding the reliability of deep learning (DL) predictions, and critical for deploying DL in the clinic. Differences between training and production ...datasets can lead to incorrect predictions with underestimated uncertainty. To investigate this pitfall, we benchmarked one pointwise and three approximate Bayesian DL models for predicting cancer of unknown primary, using three RNA-seq datasets with 10,968 samples across 57 cancer types. Our results highlight that simple and scalable Bayesian DL significantly improves the generalisation of uncertainty estimation. Moreover, we designed a prototypical metric-the area between development and production curve (ADP), which evaluates the accuracy loss when deploying models from development to production. Using ADP, we demonstrate that Bayesian DL improves accuracy under data distributional shifts when utilising 'uncertainty thresholding'. In summary, Bayesian DL is a promising approach for generalising uncertainty, improving performance, transparency, and safety of DL models for deployment in the real world.
Uveal melanoma (UM) is the most common intraocular tumour in adults and despite surgical or radiation treatment of primary tumours, ~50% of patients progress to metastatic disease. Therapeutic ...options for metastatic UM are limited, with clinical trials having little impact. Here we perform whole-genome sequencing (WGS) of 103 UM from all sites of the uveal tract (choroid, ciliary body, iris). While most UM have low tumour mutation burden (TMB), two subsets with high TMB are seen; one driven by germline MBD4 mutation, and another by ultraviolet radiation (UVR) exposure, which is restricted to iris UM. All but one tumour have a known UM driver gene mutation (GNAQ, GNA11, BAP1, PLCB4, CYSLTR2, SF3B1, EIF1AX). We identify three other significantly mutated genes (TP53, RPL5 and CENPE).
We concurrently examine the whole genome, transcriptome, methylome, and immune cell infiltrates in baseline tumors from 77 patients with advanced cutaneous melanoma treated with anti-PD-1 with or ...without anti-CTLA-4. We show that high tumor mutation burden (TMB), neoantigen load, expression of IFNγ-related genes, programmed death ligand expression, low PSMB8 methylation (therefore high expression), and T cells in the tumor microenvironment are associated with response to immunotherapy. No specific mutation correlates with therapy response. A multivariable model combining the TMB and IFNγ-related gene expression robustly predicts response (89% sensitivity, 53% specificity, area under the curve AUC, 0.84); tumors with high TMB and a high IFNγ signature show the best response to immunotherapy. This model validates in an independent cohort (80% sensitivity, 59% specificity, AUC, 0.79). Except for a JAK3 loss-of-function mutation, for patients who did not respond as predicted there is no obvious biological mechanism that clearly explained their outlier status, consistent with intratumor and intertumor heterogeneity in response to immunotherapy.
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•Multiomic analysis predicts response but not resistance to immunotherapy•Nonresponders had no common mechanisms of resistance•Structural rearrangements and PSMB8 promoter methylation occurred in nonresponders•JAK3 mutation was a possible resistance mechanism in a patient predicted to respond
Newell et al. used clinical features and multiomic analysis (WGS, RNAseq, immunohistochemistry, methylation) to show that IFNγ plus TMB most accurately predicted response to immunotherapy, but not resistance. No common mechanism of resistance was identified in keeping with tumor heterogeneity, and patients with clinical and molecular discordance were analyzed individually.
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