51 research outputs found
class_sz I: Overview
class_sz is a versatile and robust code in C and Python that can compute
theoretical predictions for a wide range of observables relevant to
cross-survey science in the Stage IV era. The code is public at
https://github.com/CLASS-SZ/class_sz along with a series of tutorial notebooks
(https://github.com/CLASS-SZ/notebooks). It will be presented in full detail in
paper II. Here we give a brief overview of key features and usage.Comment: to appear in Proc. of the mm Universe 2023 conference, Grenoble
(France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of
conferences, EDP Science
Altered processing of sensory stimuli in patients with migraine
Migraine is a cyclic disorder, in which functional and morphological brain changes fluctuate over time, culminating periodically in an attack. In the migrainous brain, temporal processing of external stimuli and sequential recruitment of neuronal networks are often dysfunctional. These changes reflect complex CNS dysfunction patterns. Assessment of multimodal evoked potentials and nociceptive reflex responses can reveal altered patterns of the brain's electrophysiological activity, thereby aiding our understanding of the pathophysiology of migraine. In this Review, we summarize the most important findings on temporal processing of evoked and reflex responses in migraine. Considering these data, we propose that thalamocortical dysrhythmia may be responsible for the altered synchronicity in migraine. To test this hypothesis in future research, electrophysiological recordings should be combined with neuroimaging studies so that the temporal patterns of sensory processing in patients with migraine can be correlated with the accompanying anatomical and functional changes
A Measurement of Gravitational Lensing of the Cosmic Microwave Background Using SPT-3G 2018 Data
We present a measurement of gravitational lensing over 1500 deg of the
Southern sky using SPT-3G temperature data at 95 and 150 GHz taken in 2018. The
lensing amplitude relative to a fiducial Planck 2018 CDM cosmology is
found to be , excluding instrumental and astrophysical
systematic uncertainties. We conduct extensive systematic and null tests to
check the robustness of the lensing measurements, and report a minimum-variance
combined lensing power spectrum over angular multipoles of , which
we use to constrain cosmological models. When analyzed alone and jointly with
primary cosmic microwave background (CMB) spectra within the CDM
model, our lensing amplitude measurements are consistent with measurements from
SPT-SZ, SPTpol, ACT, and Planck. Incorporating loose priors on the baryon
density and other parameters including uncertainties on a foreground bias
template, we obtain a constraint on using the SPT-3G 2018 lensing data alone, where
is a common measure of the amplitude of structure today and
is the matter density parameter. Combining SPT-3G 2018 lensing
measurements with baryon acoustic oscillation (BAO) data, we derive parameter
constraints of , , and Hubble constant
km s Mpc. Using CMB anisotropy and lensing measurements from
SPT-3G only, we provide independent constraints on the spatial curvature of
(95% C.L.) and the dark energy density
of (68% C.L.). When combining SPT-3G
lensing data with SPT-3G CMB anisotropy and BAO data, we find an upper limit on
the sum of the neutrino masses of eV (95% C.L.)
Mass calibration of DES Year-3 clusters via SPT-3G CMB cluster lensing
We measure the stacked lensing signal in the direction of galaxy clusters in the Dark Energy Survey Year 3 (DES Y3) redMaPPer sample, using cosmic microwave background (CMB) temperature data from SPT-3G, the third-generation CMB camera on the South Pole Telescope (SPT). Here, we estimate the lensing signal using temperature maps constructed from the initial 2 years of data from the SPT-3G 'Main' survey, covering 1500 deg2 of the Southern sky. We then use this lensing signal as a proxy for the mean cluster mass of the DES sample. The thermal Sunyaev-Zel'dovich (tSZ) signal, which can contaminate the lensing signal if not addressed, is isolated and removed from the data before obtaining the mass measurement. In this work, we employ three versions of the redMaPPer catalogue: a Flux-Limited sample containing 8865 clusters, a Volume-Limited sample with 5391 clusters, and a Volume&Redshift-Limited sample with 4450 clusters. For the three samples, we detect the CMB lensing signal at a significance of 12.4σ, 10.5σ and 10.2σ and find the mean cluster masses to be M 200m = 1.66±0.13 [stat.]± 0.03 [sys.], 1.97±0.18 [stat.]± 0.05 [sys.], and 2.11±0.20 [stat.]± 0.05 [sys.]×1014 M⊙, respectively. This is a factor of ∼ 2 improvement relative to the precision of measurements with previous generations of SPT surveys and the most constraining cluster mass measurements using CMB cluster lensing to date. Overall, we find no significant tensions between our results and masses given by redMaPPer mass-richness scaling relations of previous works, which were calibrated using CMB cluster lensing, optical weak lensing, and velocity dispersion measurements from various combinations of DES, SDSS and Planck data. We then divide our sample into 3 redshift and 3 richness bins, finding no significant discrepancies with optical weak-lensing calibrated masses in these bins. We forecast a 5.7% constraint on the mean cluster mass of the DES Y3 sample with the complete SPT-3G surveys when using both temperature and polarization data and including an additional ∼ 1400 deg2 of observations from the 'Extended' SPT-3G survey
Inflammatory Components of the Thyroid Cancer Microenvironment: An Avenue for Identification of Novel Biomarkers
The incidence of thyroid cancer in the United States is on the rise with an appreciably high disease recurrence rate of 20-30%. Anaplastic thyroid cancer (ATC), although rare in occurrence, is an aggressive form of cancer with limited treatment options and bleak cure rates. This chapter uses discussions of in vitro models that are representative of papillary, anaplastic, and follicular thyroid cancer to evaluate the crosstalk between specific cells of the tumor microenvironment (TME), which serves as a highly heterogeneous realm of signaling cascades and metabolism that are associated with tumorigenesis. The cellular constituents of the TME carry out varying characteristic immunomodulatory functions that are discussed throughout this chapter. The aforementioned cell types include cancer-associated fibroblasts (CAFs), endothelial cells (ECs), and cancer stem cells (CSCs), as well as specific immune cells, including natural killer (NK) cells, dendritic cells (DCs), mast cells, T regulatory (Treg) cells, CD8+ T cells, and tumor-associated macrophages (TAMs). TAM-mediated inflammation is associated with a poor prognosis of thyroid cancer, and the molecular basis of the cellular crosstalk between macrophages and thyroid cancer cells with respect to inducing a metastatic phenotype is not yet known. The dynamic nature of the physiological transition to pathological metastatic phenotypes when establishing the TME encompasses a wide range of characteristics that are further explored within this chapter, including the roles of somatic mutations and epigenetic alterations that drive the genetic heterogeneity of cancer cells, allowing for selective advantages that aid in their proliferation. Induction of these proliferating cells is typically accomplished through inflammatory induction, whereby chronic inflammation sets up a constant physiological state of inflammatory cell recruitment. The secretions of these inflammatory cells can alter the genetic makeup of proliferating cells, which can in turn, promote tumor growth.This chapter also presents an in-depth analysis of molecular interactions within the TME, including secretory cytokines and exosomes. Since the exosomal cargo of a cell is a reflection and fingerprint of the originating parental cells, the profiling of exosomal miRNA derived from thyroid cancer cells and macrophages in the TME may serve as an important step in biomarker discovery. Identification of a distinct set of tumor suppressive miRNAs downregulated in ATC-secreted exosomes indicates their role in the regulation of tumor suppressive genes that may increase the metastatic propensity of ATC. Additionally, the high expression of pro-inflammatory cytokines in studies looking at thyroid cancer and activated macrophage conditioned media suggests the existence of an inflammatory TME in thyroid cancer. New findings are suggestive of the presence of a metastatic niche in ATC tissues that is influenced by thyroid tumor microenvironment secretome-induced epithelial to mesenchymal transition (EMT), mediated by a reciprocal interaction between the pro-inflammatory M1 macrophages and the thyroid cancer cells. Thus, targeting the metastatic thyroid carcinoma microenvironment could offer potential therapeutic benefits and should be explored further in preclinical and translational models of human metastatic thyroid cancer
EHMTI-0125. Studying the permeability of the blood-brain barrier during migraine attacks using [11C]-dihydroergotamine
class_sz I: Overview
International audienceclass_sz is a versatile and robust code in C and Python that can compute theoretical predictions for a wide range of observables relevant to cross-survey science in the Stage IV era. The code is public at https://github.com/CLASS-SZ/class_sz along with a series of tutorial notebooks (https://github.com/CLASS-SZ/notebooks). It will be presented in full detail in paper II. Here we give a brief overview of key features and usage
class_sz I: Overview
International audienceclass_sz is a versatile and robust code in C and Python that can compute theoretical predictions for a wide range of observables relevant to cross-survey science in the Stage IV era. The code is public at https://github.com/CLASS-SZ/class_sz along with a series of tutorial notebooks (https://github.com/CLASS-SZ/notebooks). It will be presented in full detail in paper II. Here we give a brief overview of key features and usage
CTLA-4 blockade drives loss of T<sub>reg</sub> stability in glycolysis-low tumours.
Limiting metabolic competition in the tumour microenvironment may increase the effectiveness of immunotherapy. Owing to its crucial role in the glucose metabolism of activated T cells, CD28 signalling has been proposed as a metabolic biosensor of T cells <sup>1</sup> . By contrast, the engagement of CTLA-4 has been shown to downregulate T cell glycolysis <sup>1</sup> . Here we investigate the effect of CTLA-4 blockade on the metabolic fitness of intra-tumour T cells in relation to the glycolytic capacity of tumour cells. We found that CTLA-4 blockade promotes metabolic fitness and the infiltration of immune cells, especially in glycolysis-low tumours. Accordingly, treatment with anti-CTLA-4 antibodies improved the therapeutic outcomes of mice bearing glycolysis-defective tumours. Notably, tumour-specific CD8 <sup>+</sup> T cell responses correlated with phenotypic and functional destabilization of tumour-infiltrating regulatory T (T <sub>reg</sub> ) cells towards IFNγ- and TNF-producing cells in glycolysis-defective tumours. By mimicking the highly and poorly glycolytic tumour microenvironments in vitro, we show that the effect of CTLA-4 blockade on the destabilization of T <sub>reg</sub> cells is dependent on T <sub>reg</sub> cell glycolysis and CD28 signalling. These findings indicate that decreasing tumour competition for glucose may facilitate the therapeutic activity of CTLA-4 blockade, thus supporting its combination with inhibitors of tumour glycolysis. Moreover, these results reveal a mechanism by which anti-CTLA-4 treatment interferes with T <sub>reg</sub> cell function in the presence of glucose
Correlation Between Ground Motion Parameters and Target Displacement of Steel Structures
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