Serum Amyloid A Proteins Induce Pathogenic Th17 Cells and Promote Inflammatory Disease.

Lymphoid cells that produce interleukin (IL)-17 cytokines protect barrier tissues from pathogenic microbes but are also prominent effectors of inflammation and autoimmune disease. T helper 17 (Th17) cells, defined by RORγt-dependent production of IL-17A and IL-17F, exert homeostatic functions in the gut upon microbiota-directed differentiation from naive CD4+ T cells. In the non-pathogenic setting, their cytokine production is regulated by serum amyloid A proteins (SAA1 and SAA2) secreted by adjacent intestinal epithelial cells. However, Th17 cell behaviors vary markedly according to their environment. Here, we show that SAAs additionally direct a pathogenic pro-inflammatory Th17 cell differentiation program, acting directly on T cells in collaboration with STAT3-activating cytokines. Using loss- and gain-of-function mouse models, we show that SAA1, SAA2, and SAA3 have distinct systemic and local functions in promoting Th17-mediated inflammatory diseases. These studies suggest that T cell signaling pathways modulated by the SAAs may be attractive targets for anti-inflammatory therapies.

Transcription factor RORα enforces stability of the Th17 cell effector program by binding to a Rorc cis-regulatory element.

T helper 17 (Th17) cells regulate mucosal barrier defenses but also promote multiple autoinflammatory diseases. Although many molecular determinants of Th17 cell differentiation have been elucidated, the transcriptional programs that sustain Th17 cells in vivo remain obscure. The transcription factor RORγt is critical for Th17 cell differentiation; however, it is not clear whether the closely related RORα, which is co-expressed in Th17 cells, has a distinct role. Here, we demonstrated that although dispensable for Th17 cell differentiation, RORα was necessary for optimal Th17 responses in peripheral tissues. The absence of RORα in T cells led to reductions in both RORγt expression and effector function among Th17 cells. Cooperative binding of RORα and RORγt to a previously unidentified Rorc cis-regulatory element was essential for Th17 lineage maintenance in vivo. These data point to a non-redundant role of RORα in Th17 lineage maintenance via reinforcement of the RORγt transcriptional program.

An IL-23R/IL-22 Circuit Regulates Epithelial Serum Amyloid A to Promote Local Effector Th17 Responses.

RORγt(+) Th17 cells are important for mucosal defenses but also contribute to autoimmune disease. They accumulate in the intestine in response to microbiota and produce IL-17 cytokines. Segmented filamentous bacteria (SFB) are Th17-inducing commensals that potentiate autoimmunity in mice. RORγt(+) T cells were induced in mesenteric lymph nodes early after SFB colonization and distributed across different segments of the gastrointestinal tract. However, robust IL-17A production was restricted to the ileum, where SFB makes direct contact with the epithelium and induces serum amyloid A proteins 1 and 2 (SAA1/2), which promote local IL-17A expression in RORγt(+) T cells. We identified an SFB-dependent role of type 3 innate lymphoid cells (ILC3), which secreted IL-22 that induced epithelial SAA production in a Stat3-dependent manner. This highlights the critical role of tissue microenvironment in activating effector functions of committed Th17 cells, which may have important implications for how these cells contribute to inflammatory disease.

Partitioning of diluted anyons reveals their braiding statistics.

Correlations of partitioned particles carry essential information about their quantumness1. Partitioning full beams of charged particles leads to current fluctuations, with their autocorrelation (namely, shot noise) revealing the particles' charge2,3. This is not the case when a highly diluted beam is partitioned. Bosons or fermions will exhibit particle antibunching (owing to their sparsity and discreteness)4-6. However, when diluted anyons, such as quasiparticles in fractional quantum Hall states, are partitioned in a narrow constriction, their autocorrelation reveals an essential aspect of their quantum exchange statistics: their braiding phase7. Here we describe detailed measurements of weakly partitioned, highly diluted, one-dimension-like edge modes of the one-third filling fractional quantum Hall state. The measured autocorrelation agrees with our theory of braiding anyons in the time domain (instead of braiding in space); with a braiding phase of 2θ = 2π/3, without any fitting parameters. Our work offers a relatively straightforward and simple method to observe the braiding statistics of exotic anyonic states, such as non-abelian states8, without resorting to complex interference experiments9.

ETV5 promotes lupus pathogenesis and follicular helper T cell differentiation by inducing osteopontin expression.

Follicular helper T (TFH) cells mediate germinal center reactions to generate high affinity antibodies against specific pathogens, and their excessive production is associated with the pathogenesis of systemic autoimmune diseases such as systemic lupus erythematosus (SLE). ETV5, a member of the ETS transcription factor family, promotes TFH cell differentiation in mice. In this study, we examined the role of ETV5 in the pathogenesis of lupus in mice and humans. T cell-specific deletion of Etv5 alleles ameliorated TFH cell differentiation and autoimmune phenotypes in lupus mouse models. Further, we identified SPP1 as an ETV5 target that promotes TFH cell differentiation in both mice and humans. Notably, extracellular osteopontin (OPN) encoded by SPP1 enhances TFH cell differentiation by activating the CD44-AKT signaling pathway. Furthermore, ETV5 and SPP1 levels were increased in CD4+ T cells from patients with SLE and were positively correlated with disease activity. Taken together, our findings demonstrate that ETV5 is a lupus-promoting transcription factor, and secreted OPN promotes TFH cell differentiation.

Heterogeneous integration of single-crystalline complex-oxide membranes.

Complex-oxide materials exhibit a vast range of functional properties desirable for next-generation electronic, spintronic, magnetoelectric, neuromorphic, and energy conversion storage devices1-4. Their physical functionalities can be coupled by stacking layers of such materials to create heterostructures and can be further boosted by applying strain5-7. The predominant method for heterogeneous integration and application of strain has been through heteroepitaxy, which drastically limits the possible material combinations and the ability to integrate complex oxides with mature semiconductor technologies. Moreover, key physical properties of complex-oxide thin films, such as piezoelectricity and magnetostriction, are severely reduced by the substrate clamping effect. Here we demonstrate a universal mechanical exfoliation method of producing freestanding single-crystalline membranes made from a wide range of complex-oxide materials including perovskite, spinel and garnet crystal structures with varying crystallographic orientations. In addition, we create artificial heterostructures and hybridize their physical properties by directly stacking such freestanding membranes with different crystal structures and orientations, which is not possible using conventional methods. Our results establish a platform for stacking and coupling three-dimensional structures, akin to two-dimensional material-based heterostructures, for enhancing device functionalities8,9.

Transcriptional downregulation of S1pr1 is required for the establishment of resident memory CD8+ T cells.

Cell-mediated immunity critically depends on the localization of lymphocytes at sites of infection. While some memory T cells recirculate, a distinct lineage (resident memory T cells (T(RM) cells)) are embedded in nonlymphoid tissues (NLTs) and mediate potent protective immunity. However, the defining transcriptional basis for the establishment of T(RM) cells is unknown. We found that CD8(+) T(RM) cells lacked expression of the transcription factor KLF2 and its target gene S1pr1 (which encodes S1P1, a receptor for sphingosine 1-phosphate). Forced expression of S1P1 prevented the establishment of T(RM) cells. Cytokines that induced a T(RM) cell phenotype (including transforming growth factor-ß (TGF-ß), interleukin 33 (IL-33) and tumor-necrosis factor) elicited downregulation of KLF2 expression in a pathway dependent on phosphatidylinositol-3-OH kinase (PI(3)K) and the kinase Akt, which suggested environmental regulation. Hence, regulation of KLF2 and S1P1 provides a switch that dictates whether CD8(+) T cells commit to recirculating or tissue-resident memory populations.

Author Correction: El Niño-Southern Oscillation complexity.

In this Review, the middle initial of author Kim M. Cobb was omitted. The original Review has been corrected online.

Distinct Roles of Brd2 and Brd4 in Potentiating the Transcriptional Program for Th17 Cell Differentiation.

The BET proteins are major transcriptional regulators and have emerged as new drug targets, but their functional distinction has remained elusive. In this study, we report that the BET family members Brd2 and Brd4 exert distinct genomic functions at genes whose transcription they co-regulate during mouse T helper 17 (Th17) cell differentiation. Brd2 is associated with the chromatin insulator CTCF and the cohesin complex to support cis-regulatory enhancer assembly for gene transcriptional activation. In this context, Brd2 binds the transcription factor Stat3 in an acetylation-sensitive manner and facilitates Stat3 recruitment to active enhancers occupied with transcription factors Irf4 and Batf. In parallel, Brd4 temporally controls RNA polymerase II (Pol II) processivity during transcription elongation through cyclin T1 and Cdk9 recruitment and Pol II Ser2 phosphorylation. Collectively, our study uncovers both separate and interdependent Brd2 and Brd4 functions in potentiating the genetic program required for Th17 cell development and adaptive immunity.

Selective sweeps in SARS-CoV-2 variant competition.

The main mathematical result in this paper is that change of variables in the ordinary differential equation (ODE) for the competition of two infections in a Susceptible-Infected-Removed (SIR) model shows that the fraction of cases due to the new variant satisfies the logistic differential equation, which models selective sweeps. Fitting the logistic to data from the Global Initiative on Sharing All Influenza Data (GISAID) shows that this correctly predicts the rapid turnover from one dominant variant to another. In addition, our fitting gives sensible estimates of the increase in infectivity. These arguments are applicable to any epidemic modeled by SIR equations.

The transcription factor KLF2 restrains CD4⁺ T follicular helper cell differentiation.

T follicular helper (Tfh) cells are essential for efficient B cell responses, yet the factors that regulate differentiation of this CD4(+) T cell subset are incompletely understood. Here we found that the KLF2 transcription factor serves to restrain Tfh cell generation. Induced KLF2 deficiency in activated CD4(+) T cells led to increased Tfh cell generation and B cell priming, whereas KLF2 overexpression prevented Tfh cell production. KLF2 promotes expression of the trafficking receptor S1PR1, and S1PR1 downregulation is essential for efficient Tfh cell production. However, KLF2 also induced expression of the transcription factor Blimp-1, which repressed transcription factor Bcl-6 and thereby impaired Tfh cell differentiation. Furthermore, KLF2 induced expression of the transcription factors T-bet and GATA3 and enhanced Th1 differentiation. Hence, our data indicate KLF2 is pivotal for coordinating CD4(+) T cell differentiation through two distinct and complementary mechanisms: via control of T cell localization and by regulation of lineage-defining transcription factors.

Human glioblastoma arises from subventricular zone cells with low-level driver mutations.

Glioblastoma (GBM) is a devastating and incurable brain tumour, with a median overall survival of fifteen months1,2. Identifying the cell of origin that harbours mutations that drive GBM could provide a fundamental basis for understanding disease progression and developing new treatments. Given that the accumulation of somatic mutations has been implicated in gliomagenesis, studies have suggested that neural stem cells (NSCs), with their self-renewal and proliferative capacities, in the subventricular zone (SVZ) of the adult human brain may be the cells from which GBM originates3-5. However, there is a lack of direct genetic evidence from human patients with GBM4,6-10. Here we describe direct molecular genetic evidence from patient brain tissue and genome-edited mouse models that show astrocyte-like NSCs in the SVZ to be the cell of origin that contains the driver mutations of human GBM. First, we performed deep sequencing of triple-matched tissues, consisting of (i) normal SVZ tissue away from the tumour mass, (ii) tumour tissue, and (iii) normal cortical tissue (or blood), from 28 patients with isocitrate dehydrogenase (IDH) wild-type GBM or other types of brain tumour. We found that normal SVZ tissue away from the tumour in 56.3% of patients with wild-type IDH GBM contained low-level GBM driver mutations (down to approximately 1% of the mutational burden) that were observed at high levels in their matching tumours. Moreover, by single-cell sequencing and laser microdissection analysis of patient brain tissue and genome editing of a mouse model, we found that astrocyte-like NSCs that carry driver mutations migrate from the SVZ and lead to the development of high-grade malignant gliomas in distant brain regions. Together, our results show that NSCs in human SVZ tissue are the cells of origin that contain the driver mutations of GBM.

El Niño-Southern Oscillation complexity.

El Niño events are characterized by surface warming of the tropical Pacific Ocean and weakening of equatorial trade winds that occur every few years. Such conditions are accompanied by changes in atmospheric and oceanic circulation, affecting global climate, marine and terrestrial ecosystems, fisheries and human activities. The alternation of warm El Niño and cold La Niña conditions, referred to as the El Niño-Southern Oscillation (ENSO), represents the strongest year-to-year fluctuation of the global climate system. Here we provide a synopsis of our current understanding of the spatio-temporal complexity of this important climate mode and its influence on the Earth system.

Scalable High-Precision Trimming of Photonic Resonances by Polymer Exposure to Energetic Beams.

Integrated photonic circuits (PICs) have seen an explosion in interest, through to commercialization in the past decade. Most PICs rely on sharp resonances to modulate, steer, and multiplex signals. However, the spectral characteristics of high-quality resonances are highly sensitive to small variations in fabrication and material constants, which limits their applicability. Active tuning mechanisms are commonly employed to account for such deviations, consuming energy and occupying valuable chip real estate. Readily employable, accurate, and highly scalable mechanisms to tailor the modal properties of photonic integrated circuits are urgently required. Here, we present an elegant and powerful solution to achieve this in a scalable manner during the semiconductor fabrication process using existing lithography tools: by exploiting the volume shrinkage exhibited by certain polymers to permanently modulate the waveguide's effective index. This technique enables broadband and lossless tuning with immediate applicability in wide-ranging applications in optical computing, telecommunications, and free-space optics.

ERK mediates interferon gamma-induced melanoma cell death.

BACKGROUND: Interferon-gamma (IFNγ) exerts potent growth inhibitory effects on a wide range of cancer cells through unknown signaling pathways. We pursued complementary screening approaches to characterize the growth inhibition pathway. METHODS: We performed chemical genomics and whole genome targeting CRISPR/Cas9 screens using patient-derived melanoma lines to uncover essential nodes in the IFNγ-mediated growth inhibition pathway. We used transcriptomic profiling to identify cell death pathways activated upon IFNγ exposure. Live imaging experiments coupled with apoptosis assays confirmed the involvement of these pathways in IFNγ-mediated cell death. RESULTS: We show that IFNγ signaling activated ERK. Blocking ERK activation rescued IFNγ-mediated apoptosis in 17 of 23 (~ 74%) cell lines representing BRAF, NRAS, NF1 mutant, and triple wild type subtypes of cutaneous melanoma. ERK signaling induced a stress response, ultimately leading to apoptosis through the activity of DR5 and NOXA proteins. CONCLUSIONS: Our results provide a new understanding of the IFNγ growth inhibition pathway, which will be crucial in defining mechanisms of immunotherapy response and resistance.

Radiologist's Guide to Evaluating Publications of Clinical Research on AI: How We Do It.

Literacy in research studies of artificial intelligence (AI) has become an important skill for radiologists. It is required to make a proper assessment of the validity, reproducibility, and clinical applicability of AI studies. However, AI studies are generally perceived to be more difficult for clinician readers to evaluate than traditional clinical research studies. This special report-as an effective, concise guide for readers-aims to assist clinical radiologists in critically evaluating different types of clinical research articles involving AI. It does not intend to be a comprehensive checklist or methodological summary for complete clinical evaluation of AI or a reporting guideline. Ten key items for readers to check are described, regarding study purpose, function and clinical context of AI, training data, data preprocessing, AI modeling techniques, test data, AI performance, helpfulness and value of AI, interpretability of AI, and code sharing. The important aspects of each item are explained for readers to consider when reading publications on AI clinical research. Evaluating each item can help radiologists assess the validity, reproducibility, and clinical applicability of clinical research articles involving AI.

Methods for Clinical Evaluation of Artificial Intelligence Algorithms for Medical Diagnosis.

Adequate clinical evaluation of artificial intelligence (AI) algorithms before adoption in practice is critical. Clinical evaluation aims to confirm acceptable AI performance through adequate external testing and confirm the benefits of AI-assisted care compared with conventional care through appropriately designed and conducted studies, for which prospective studies are desirable. This article explains some of the fundamental methodological points that should be considered when designing and appraising the clinical evaluation of AI algorithms for medical diagnosis. The specific topics addressed include the following: (a) the importance of external testing of AI algorithms and strategies for conducting the external testing effectively, (b) the various metrics and graphical methods for evaluating the AI performance as well as essential methodological points to note in using and interpreting them, (c) paired study designs primarily for comparative performance evaluation of conventional and AI-assisted diagnoses, (d) parallel study designs primarily for evaluating the effect of AI intervention with an emphasis on randomized clinical trials, and (e) up-to-date guidelines for reporting clinical studies on AI, with an emphasis on guidelines registered in the EQUATOR Network library. Sound methodological knowledge of these topics will aid the design, execution, reporting, and appraisal of clinical evaluation of AI.

Study on weight loss outcomes after bariatric surgery to determine a metric least influenced by preoperative BMI.

BACKGROUND: Percentage excess weight loss (%EWL) and percentage total weight loss (%TWL) are used for reporting outcomes after bariatric surgery. However, they are not ideal for comparing outcomes on populations of varied initial body mass index (BMI). This study aimed to validate a recently introduced metric - percentage alterable weight loss (%AWL), after laparoscopic sleeve gastrectomy (LSG) and Roux-en-Y gastric bypass (LRYGB). METHODS: Analysis of weight data of all patients who had undergone LSG and LRYGB until the end of the year 2021. Outcomes for both procedures were analyzed separately. The patients were divided into quartile subgroups Q1 (lowest BMI) to Q4 (highest BMI) and weight loss up to 5 years postoperatively was compared using %EWL, %TWL and %AWL metrics. An intermediary metric was also tested for its effect on the weight loss patterns for both procedures. RESULTS: The cohort included 1020 LSG and 322 LRYGB patients, with initial mean BMI of 43.5 ± 7.5 and 41.9 ± 8.3 kg/m2, respectively. %EWL significantly favors lower BMI subgroups for both procedures. %TWL is ideal for comparing weight loss during the first 6 months but it then favors higher BMI subgroups beyond 6 months. %AWL with reference BMI of 13 kg/m2 seems the best metric for medium-term comparison of weight loss for LRYGB and an intermediary metric based on BMI 8 kg/m2 provides the best fit for medium-term comparison for LSG. CONCLUSIONS: %TWL is least influenced by initial BMI during short-term follow-up after LSG and LRYGB. For medium-term comparison, %AWL is best suited for LRYGB while an intermediary metric is found to provide the best fit for LSG.