Explore the vast range of titles available.

Unprecedented quantities of heat are entering the Pacific sector of the Arctic Ocean through Bering Strait, particularly during summer months. Though some heat is lost to the atmosphere during autumn cooling, a significant fraction of the incoming warm, salty water subducts (dives beneath) below a cooler fresher layer of near-surface water, subsequently extending hundreds of kilometers into the Beaufort Gyre. Upward turbulent mixing of these sub-surface pockets of heat is likely accelerating sea ice melt in the region. This Pacific-origin water brings both heat and unique biogeochemical properties, contributing to a changing Arctic ecosystem. However, our ability to understand or forecast the role of this incoming water mass has been hampered by lack of understanding of the physical processes controlling subduction and evolution of this this warm water. Crucially, the processes seen here occur at small horizontal scales not resolved by regional forecast models or climate simulations; new parameterizations must be developed that accurately represent the physics. Here we present novel high resolution observations showing the detailed process of subduction and initial evolution of warm Pacific-origin water in the southern Beaufort Gyre. Warming ocean water plays a significant role in accelerating Arctic sea ice melt. Here the authors present detailed observations of warm water of Pacific origin entering and diving beneath the Arctic ocean surface, and explore the dynamical processes governing its evolution.

The identification of lymphocyte subsets with non-overlapping effector functions has been pivotal to the development of targeted therapies in immune-mediated inflammatory diseases (IMIDs) 1 , 2 . However, it remains unclear whether fibroblast subclasses with non-overlapping functions also exist and are responsible for the wide variety of tissue-driven processes observed in IMIDs, such as inflammation and damage 3 , 4 – 5 . Here we identify and describe the biology of distinct subsets of fibroblasts responsible for mediating either inflammation or tissue damage in arthritis. We show that deletion of fibroblast activation protein-α (FAPα) + fibroblasts suppressed both inflammation and bone erosions in mouse models of resolving and persistent arthritis. Single-cell transcriptional analysis identified two distinct fibroblast subsets within the FAPα + population: FAPα + THY1 + immune effector fibroblasts located in the synovial sub-lining, and FAPα + THY1 − destructive fibroblasts restricted to the synovial lining layer. When adoptively transferred into the joint, FAPα + THY1 − fibroblasts selectively mediate bone and cartilage damage with little effect on inflammation, whereas transfer of FAPα + THY1 + fibroblasts resulted in a more severe and persistent inflammatory arthritis, with minimal effect on bone and cartilage. Our findings describing anatomically discrete, functionally distinct fibroblast subsets with non-overlapping functions have important implications for cell-based therapies aimed at modulating inflammation and tissue damage. Distinct subsets of fibroblasts, which differ in their expression of thymus cell antigen 1 (THY1), are responsible for inflammation and tissue damage in mouse models of arthritis.

The inverse problem of designing component interactions to target emergent structure is fundamental to numerous applications in biotechnology, materials science, and statistical physics. Equally important is the inverse problem of designing emergent kinetics, but this has received considerably less attention. Using recent advances in automatic differentiation, we show how kinetic pathways can be precisely designed by directly differentiating through statistical physics models, namely free energy calculations and molecular dynamics simulations. We consider two systems that are crucial to our understanding of structural self-assembly: bulk crystallization and small nanoclusters. In each case, we are able to assemble precise dynamical features. Using gradient information, we manipulate interactions among constituent particles to tune the rate at which these systems yield specific structures of interest. Moreover, we use this approach to learn nontrivial features about the high-dimensional design space, allowing us to accurately predict when multiple kinetic features can be simultaneously and independently controlled. These results provide a concrete and generalizable foundation for studying nonstructural self-assembly, including kinetic properties as well as other complex emergent properties, in a vast array of systems.

The U.S. Department of Energy Systems Biology Knowledgebase (KBase, http://kbase.us) is an open-source software and data platform designed to tackle the grand challenge of systems biology—predicting and designing biological function at scales ranging from the biomolecular to the ecological. KBase is available for anyone to use, and enables researchers to collaboratively generate, test, compare, and share hypotheses about biological functions; perform large analyses on scalable computing infrastructure; and combine experimental evidence and conclusions to model plant and microbial physiology and community dynamics. The KBase platform has extensible analytical capabilities that currently include (meta)genome assembly, annotation, comparative genomics, transcriptomics, and metabolic modeling; a web-based user interface that supports building, sharing, and publishing reproducible and well-annotated analyses with integrated data; and a software development kit that enables the community to add functionality to the system.

CD1d-restricted natural killer T (NKT) cells include two major subgroups. The most widely studied are Vα14Jα18 ⁺ invariant NKT (iNKT) cells that recognize the prototypical α-galactosylceramide antigen, whereas the other major group uses diverse T-cell receptor (TCR) α-and β-chains, does not recognize α-galactosylceramide, and is referred to as diverse NKT (dNKT) cells. dNKT cells play important roles during infection and autoimmunity, but the antigens they recognize remain poorly understood. Here, we identified phosphatidylglycerol (PG), diphosphatidylglycerol (DPG, or cardiolipin), and phosphatidylinositol from Mycobacterium tuberculosis or Corynebacterium glutamicum as microbial antigens that stimulated various dNKT, but not iNKT, hybridomas. dNKT hybridomas showed distinct reactivities for diverse antigens. Stimulation of dNKT hybridomas by microbial PG was independent of Toll-like receptor-mediated signaling by antigen-presenting cells and required lipid uptake and/or processing. Furthermore, microbial PG bound to CD1d molecules and plate-bound PG/CD1d complexes stimulated dNKT hybridomas, indicating direct recognition by the dNKT cell TCR. Interestingly, despite structural differences in acyl chain composition between microbial and mammalian PG and DPG, lipids from both sources stimulated dNKT hybridomas, suggesting that presentation of microbial lipids and enhanced availability of stimulatory self-lipids may both contribute to dNKT cell activation during infection.

Current inflammatory bowel disease (IBD) therapies are ineffective in a high proportion of patients. Combining bulk and single-cell transcriptomics, quantitative histopathology and in situ localization across three cohorts of patients with IBD (total n  = 376), we identify coexpressed gene modules within the heterogeneous tissular inflammatory response in IBD that map to distinct histopathological and cellular features (pathotypes). One of these pathotypes is defined by high neutrophil infiltration, activation of fibroblasts and vascular remodeling at sites of deep ulceration. Activated fibroblasts in the ulcer bed display neutrophil-chemoattractant properties that are IL-1R, but not TNF, dependent. Pathotype-associated neutrophil and fibroblast signatures are increased in nonresponders to several therapies across four independent cohorts (total n  = 343). The identification of distinct, localized, tissular pathotypes will aid precision targeting of current therapeutics and provides a biological rationale for IL-1 signaling blockade in ulcerating disease. Transcriptomic and histological profiling of gut biopsies from multiple independent cohorts of patients with inflammatory bowel disease identifies distinct histopathological, molecular and cellular features associated with treatment response, providing insights for patient stratification and precision therapy.

Accurate representation of the turbulent exchange of carbon, water, and heat between the land surface and the atmosphere is critical for modelling global energy, water, and carbon cycles in both future climate projections and weather forecasts. Evaluation of models' ability to do this is performed in a wide range of simulation environments, often without explicit consideration of the degree of observational constraint or uncertainty and typically without quantification of benchmark performance expectations. We describe a Model Intercomparison Project (MIP) that attempts to resolve these shortcomings, comparing the surface turbulent heat flux predictions of around 20 different land models provided with in situ meteorological forcing evaluated with measured surface fluxes using quality-controlled data from 170 eddy-covariance-based flux tower sites. Predictions from seven out-of-sample empirical models are used to quantify the information available to land models in their forcing data and so the potential for land model performance improvement. Sites with unusual behaviour, complicated processes, poor data quality, or uncommon flux magnitude are more difficult to predict for both mechanistic and empirical models, providing a means of fairer assessment of land model performance. When examining observational uncertainty, model performance does not appear to improve in low-turbulence periods or with energy-balance-corrected flux tower data, and indeed some results raise questions about whether the energy balance correction process itself is appropriate. In all cases the results are broadly consistent, with simple out-of-sample empirical models, including linear regression, comfortably outperforming mechanistic land models. In all but two cases, latent heat flux and net ecosystem exchange of CO2 are better predicted by land models than sensible heat flux, despite it seeming to have fewer physical controlling processes. Land models that are implemented in Earth system models also appear to perform notably better than stand-alone ecosystem (including demographic) models, at least in terms of the fluxes examined here. The approach we outline enables isolation of the locations and conditions under which model developers can know that a land model can improve, allowing information pathways and discrete parameterisations in models to be identified and targeted for future model development.

Background/Objectives: Ovarian cancer (OC) remains the most lethal gynecologic malignancy, largely due to late-stage diagnosis and high rates of recurrence following platinum-based chemotherapy. Growing evidence implicates cancer stem-like cells (CSCs) in OC relapse, as these cells exhibit enhanced chemoresistance, stemness, epithelial–mesenchymal transition (EMT), and the capacity to remodel the tumor microenvironment. Inhibitors of DNA-binding (ID) 1-4 proteins are transcription factors with known redundancy; however, their collective role in OC chemotherapy response remains poorly defined. Here, we examined how ID family signaling responds to chemotherapy and contributes to CSC-associated features and microenvironment remodeling. Methods: Publicly available patient data, OC cell lines, and a subcutaneous xenograft mouse model were used to correlate changes in ID1-4 expression with CSCs, EMT, and the tumor microenvironment (TME). OC cell lines were used for in vitro assays to evaluate CSC features and IL-6 production in the presence of carboplatin and/or a small molecule inhibitor of ID proteins, AGX51. Results: Analysis of clinical datasets, cell lines, and in vivo models revealed enrichment of ID1-4 following chemotherapy, with additive increases across treatment cycles. In vivo ID2 and ID4 expression was associated with IL-6 secretion and loss of anti-tumoral macrophages. Pan-ID inhibition demonstrated that cumulative ID activity minimally supports CSC maintenance during chemotherapy, while more strongly regulating IL-6 secretion. Conclusions: IL-6 production from cancer cells was at least partially dependent on ID proteins, linking collective ID signaling to microenvironment remodeling and relapse potential in ovarian cancer.

To the Editor: Eskander et al. (Nov. 14 issue) 1 provide a thorough review of acute upper airway obstruction. However, the authors do not describe the importance of preprocedural assessment of airway risk, with consideration of the technique of tracheal intubation in a patient who is awake (known as “awake tracheal intubation”) to secure an obstructed airway. Throughout their description, the authors describe the value and use of the Difficult Airway Society (DAS) algorithm for management of unanticipated difficult intubation. 2 However, in the context of anticipated difficulty (as commonly encountered with the presentation of acute upper airway obstruction), existing guidelines recommend . . .