Opportunistic CT screening leverages robust imaging data embedded within abdominal and thoracic scans that are generally unrelated to the specific clinical indication and have heretofore gone largely ...unused. This incidental imaging information may prove beneficial to patients in terms of wellness, prevention, risk profiling, and presymptomatic detection of relevant disease. The growing interest in CT-based opportunistic screening relates to a confluence of factors: the objective and generalizable nature of CT-based body composition measures, the emergence of fully automated explainable AI solutions, the sheer volume of body CT scans performed, and the increasing emphasis on precision medicine and value-added initiatives. With a systematic approach to body composition and other useful CT markers, initial evidence suggests that their ability to help radiologists assess biologic age and predict future adverse cardiometabolic events rivals even the best available clinical reference standards. Emerging data suggest that standalone "intended" CT screening over an unorganized opportunistic approach may be justified, especially when combined with established cancer screening. This review will discuss the current status of opportunistic CT screening, including specific body composition markers and the various disease processes that may be impacted. The remaining hurdles to widespread clinical adoption include generalization to more diverse patient populations, disparate technical settings, and reimbursement.
Impaired insulin-mediated suppression of hepatic glucose production (HGP) plays a major role in the pathogenesis of type 2 diabetes (T2D), yet the molecular mechanism by which this occurs remains ...unknown. Using a novel in vivo metabolomics approach, we show that the major mechanism by which insulin suppresses HGP is through reductions in hepatic acetyl CoA by suppression of lipolysis in white adipose tissue (WAT) leading to reductions in pyruvate carboxylase flux. This mechanism was confirmed in mice and rats with genetic ablation of insulin signaling and mice lacking adipose triglyceride lipase. Insulin’s ability to suppress hepatic acetyl CoA, PC activity, and lipolysis was lost in high-fat-fed rats, a phenomenon reversible by IL-6 neutralization and inducible by IL-6 infusion. Taken together, these data identify WAT-derived hepatic acetyl CoA as the main regulator of HGP by insulin and link it to inflammation-induced hepatic insulin resistance associated with obesity and T2D.
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•Insulin inhibits gluconeogenesis by suppressing lipolysis and hepatic acetyl CoA•Hyperglycemia associated with HFD is due to increased WAT-derived hepatic acetyl CoA•ATGL KOs are protected from HFD-induced insulin resistance due to decreased lipolysis•mφJNK KOs are protected from HFD-induced insulin resistance due to decreased lipolysis
Metabolic abnormalities associated with a high-fat diet are found to be driven by increased hepatic acetyl CoA levels, which are shown to be a consequence of white adipose tissue inflammation and inappropriately increased lipolysis.
Nearly 60 CCCH zinc finger proteins have been identified in humans and mice. These proteins are involved in the regulation of multiple steps of RNA metabolism, including mRNA splicing, ...polyadenylation, transportation, translation and decay. Several CCCH zinc finger proteins, such as tristetraprolin (TTP), roquin 1 and MCPIP1 (also known as regnase 1), are crucial for many aspects of immune regulation by targeting mRNAs for degradation and modulation of signalling pathways. In this Review, we focus on the emerging roles of CCCH zinc finger proteins in the regulation of immune responses through their effects on cytokine production, immune cell activation and immune homeostasis.
Labeled medical imaging data is scarce and expensive to generate. To achieve generalizable deep learning models large amounts of data are needed. Standard data augmentation is a method to increase ...generalizability and is routinely performed. Generative adversarial networks offer a novel method for data augmentation. We evaluate the use of CycleGAN for data augmentation in CT segmentation tasks. Using a large image database we trained a CycleGAN to transform contrast CT images into non-contrast images. We then used the trained CycleGAN to augment our training using these synthetic non-contrast images. We compared the segmentation performance of a U-Net trained on the original dataset compared to a U-Net trained on the combined dataset of original data and synthetic non-contrast images. We further evaluated the U-Net segmentation performance on two separate datasets: The original contrast CT dataset on which segmentations were created and a second dataset from a different hospital containing only non-contrast CTs. We refer to these 2 separate datasets as the in-distribution and out-of-distribution datasets, respectively. We show that in several CT segmentation tasks performance is improved significantly, especially in out-of-distribution (noncontrast CT) data. For example, when training the model with standard augmentation techniques, performance of segmentation of the kidneys on out-of-distribution non-contrast images was dramatically lower than for in-distribution data (Dice score of 0.09 vs. 0.94 for out-of-distribution vs. in-distribution data, respectively, p < 0.001). When the kidney model was trained with CycleGAN augmentation techniques, the out-of-distribution (non-contrast) performance increased dramatically (from a Dice score of 0.09 to 0.66, p < 0.001). Improvements for the liver and spleen were smaller, from 0.86 to 0.89 and 0.65 to 0.69, respectively. We believe this method will be valuable to medical imaging researchers to reduce manual segmentation effort and cost in CT imaging.
Sequestration of CO2, either from gas mixtures or directly from air (direct air capture, DAC), could mitigate carbon emissions. Here five materials are investigated for their ability to adsorb CO2 ...directly from air and other gas mixtures. The sorbents studied are benchmark materials that encompass four types of porous material, one chemisorbent, TEPA‐SBA‐15 (amine‐modified mesoporous silica) and four physisorbents: Zeolite 13X (inorganic); HKUST‐1 and Mg‐MOF‐74/Mg‐dobdc (metal–organic frameworks, MOFs); SIFSIX‐3‐Ni, (hybrid ultramicroporous material). Temperature‐programmed desorption (TPD) experiments afforded information about the contents of each sorbent under equilibrium conditions and their ease of recycling. Accelerated stability tests addressed projected shelf‐life of the five sorbents. The four physisorbents were found to be capable of carbon capture from CO2‐rich gas mixtures, but competition and reaction with atmospheric moisture significantly reduced their DAC performance.
Five benchmark materials are investigated for their ability to adsorb CO2 directly from air. It is found that physisorbents can compete with chemisorbents with respect to CO2/N2 selectivity but direct air capture (DAC) performance is mitigated because of competition with water vapor. Optimizing pore size and pore chemistry in the presence of water vapor must be further addressed if physisorbents are to compete with chemisorbents.
This review discusses potential oncologic and nononcologic applications of CT texture analysis ( CTTA CT texture analysis ), an emerging area of "radiomics" that extracts, analyzes, and interprets ...quantitative imaging features. CTTA CT texture analysis allows objective assessment of lesion and organ heterogeneity beyond what is possible with subjective visual interpretation and may reflect information about the tissue microenvironment. CTTA CT texture analysis has shown promise in lesion characterization, such as differentiating benign from malignant or more biologically aggressive lesions. Pretreatment CT texture features are associated with histopathologic correlates such as tumor grade, tumor cellular processes such as hypoxia or angiogenesis, and genetic features such as KRAS or epidermal growth factor receptor (EGFR) mutation status. In addition, and likely as a result, these CT texture features have been linked to prognosis and clinical outcomes in some tumor types. CTTA CT texture analysis has also been used to assess response to therapy, with decreases in tumor heterogeneity generally associated with pathologic response and improved outcomes. A variety of nononcologic applications of CTTA CT texture analysis are emerging, particularly quantifying fibrosis in the liver and lung. Although CTTA CT texture analysis seems to be a promising imaging biomarker, there is marked variability in methods, parameters reported, and strength of associations with biologic correlates. Before CTTA CT texture analysis can be considered for widespread clinical implementation, standardization of tumor segmentation and measurement techniques, image filtration and postprocessing techniques, and methods for mathematically handling multiple tumors and time points is needed, in addition to identification of key texture parameters among hundreds of potential candidates, continued investigation and external validation of histopathologic correlates, and structured reporting of findings.
RSNA, 2017.
Porous materials capable of selectively capturing CO2 from flue‐gases or natural gas are of interest in terms of rising atmospheric CO2 levels and methane purification. Size‐exclusive sieving of CO2 ...over CH4 and N2 has rarely been achieved. Herein we show that a crystal engineering approach to tuning of pore‐size in a coordination network, Cu(quinoline‐5‐carboxyate)2n (Qc‐5‐Cu) ena+bles ultra‐high selectivity for CO2 over N2 (SCN≈40 000) and CH4 (SCM≈3300). Qc‐5‐Cu‐sql‐β, a narrow pore polymorph of the square lattice (sql) coordination network Qc‐5‐Cu‐sql‐α, adsorbs CO2 while excluding both CH4 and N2. Experimental measurements and molecular modeling validate and explain the performance. Qc‐5‐Cu‐sql‐β is stable to moisture and its separation performance is unaffected by humidity.
Sieves you right: Crystal engineering of supramolecular isomers of Cu(quinoline‐5‐carboxyate)2n metal–organic materials enables the right pore‐chemistry for ultra‐high CO2/N2 and CO2/CH4 selectivity even in the presence of water vapor.
A
bstract
It is shown that black hole spacetimes in classical Einstein gravity are characterized by, in addition to their ADM mass
M
, momentum
P
→
, angular momentum
J
→
and boost charge
K
→
, an ...infinite head of supertranslation hair. The distinct black holes are distinguished by classical superrotation charges measured at infinity. Solutions with super-translation hair are diffeomorphic to the Schwarzschild spacetime, but the diffeomorphisms are part of the BMS subgroup and act nontrivially on the physical phase space. It is shown that a black hole can be supertranslated by throwing in an asymmetric shock wave. A leading-order Bondi-gauge expression is derived for the linearized horizon supertranslation charge and shown to generate, via the Dirac bracket, supertranslations on the linearized phase space of gravitational excitations of the horizon. The considerations of this paper are largely classical augmented by comments on their implications for the quantum theory.
Black hole entropy and soft hair Haco, Sasha; Hawking, Stephen W.; Perry, Malcolm J. ...
The journal of high energy physics,
12/2018, Letnik:
2018, Številka:
12
Journal Article
Recenzirano
Odprti dostop
A
bstract
A set of infinitesimal Virasoro
L
⊗ Virasoro
R
diffeomorphisms are presented which act non-trivially on the horizon of a generic Kerr black hole with spin J. The covariant phase space ...formalism provides a formula for the Virasoro charges as surface integrals on the horizon. Integrability and associativity of the charge algebra are shown to require the inclusion of ‘Wald-Zoupas’ counterterms. A counterterm satisfying the known consistency requirement is constructed and yields central charges
c
L
=
c
R
= 12
J
. Assuming the existence of a quantum Hilbert space on which these charges generate the symmetries, as well as the applicability of the Cardy formula, the central charges reproduce the macroscopic area-entropy law for generic Kerr black holes.
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