A crucial component of nonalcoholic fatty liver disease (NAFLD) pathogenesis is lipid stress, which may contribute to hepatic inflammation and activation of innate immunity in the liver. However, ...little is known regarding how dietary lipids, including fat and cholesterol, may facilitate innate immune activation in vivo. We hypothesized that dietary fat and cholesterol drive NAFLD progression to steatohepatitis and hepatic fibrosis by altering the transcription and phenotype of hepatic macrophages. This hypothesis was tested by using RNA‐sequencing methods to characterize and analyze sort‐purified hepatic macrophage populations that were isolated from mice fed diets with varying amounts of fat and cholesterol. The addition of cholesterol to a high‐fat diet triggered hepatic pathology reminiscent of advanced nonalcoholic steatohepatitis (NASH) in humans characterized by signs of cholesterol dysregulation, generation of oxidized low‐density lipoprotein, increased recruitment of hepatic macrophages, and significant fibrosis. RNA‐sequencing analyses of hepatic macrophages in this model revealed that dietary cholesterol induced a tissue repair and regeneration phenotype in Kupffer cells (KCs) and recruited infiltrating macrophages to a greater degree than fat. Furthermore, comparison of diseased KCs and infiltrating macrophages revealed that these two macrophage subsets are transcriptionally diverse. Finally, direct stimulation of murine and human macrophages with oxidized low‐density lipoprotein recapitulated some of the transcriptional changes observed in the RNA‐sequencing study. These findings indicate that fat and cholesterol synergize to alter macrophage phenotype, and they also challenge the dogma that KCs are purely proinflammatory in NASH. Conclusion: This comprehensive view of macrophage populations in NASH indicates mechanisms by which cholesterol contributes to NASH progression and identifies potential therapeutic targets for this common disease.
Objective: To examine alterations in patterns of brain activation seen in normal aging and in mild Alzheimer’s disease by functional magnetic resonance imaging (fMRI) during an associative encoding ...task. Methods: 10 young controls, 10 elderly controls, and seven patients with mild Alzheimer’s disease were studied using fMRI during a face–name association encoding task. The fMRI paradigm used a block design with three conditions: novel face–name pairs, repeated face–name pairs, and visual fixation. Results: The young and elderly controls differed primarily in the pattern of activation seen in prefrontal and parietal cortices: elderly controls showed significantly less activation in both superior and inferior prefrontal cortices but greater activation in parietal regions than younger controls during the encoding of novel face–name pairs. Compared with elderly controls, the Alzheimer patients showed significantly less activation in the hippocampal formation but greater activation in the medial parietal and posterior cingulate regions. Conclusions: The pattern of fMRI activation during the encoding of novel associations is differentially altered in the early stages of Alzheimer’s disease compared with normal aging.
Results are presented from a study of variability in the UV resonance lines from the cataclysmic variable V795 Her, based on a total of 28 IUE SWP low-resolution spectra. Significant line profile ...fluctuations are evident in the C IV λ1549 and Si IV λ1400 doublets on time-scales down to ≲ 30 min. There is little or no evidence for changes in N v λ1240. Only C IV λ1549 is (occasionally) seen in emission; the morphology of this profile changes from an absorption-dominated line to an emission-dominated one in ∼ a few hours. The observed C IV and Si IV absorption strengths vary in concert. Although no correlations are evident between changes in the Si IV and C IV line strengths and the mooted orbital period of V795 Her (∼ 2.6 hr), our time-series analyses of the UV data suggest a ∼ 4.8-hr periodic modulation in the line profile variability. Constraints on the origin and geometry of the line formation are discussed, based on these UV data. We consider in particular whether: (i) a continuum-emitting hotspot on the disc, or (ii) wind outflow asymmetry could account for the regular line profile variability. There is freedom in specifying both types of model to ensure that both can reproduce the extent of the observed profile changes, but neither yields the appropriate phase dependence. Alternative specifications for departures from axial symmetry are suggested.
The high comorbidity among neuropsychiatric disorders suggests a possible common neurobiological phenotype. Resting-state regional cerebral blood flow (CBF) can be measured noninvasively with ...magnetic resonance imaging (MRI) and abnormalities in regional CBF are present in many neuropsychiatric disorders. Regional CBF may also provide a useful biological marker across different types of psychopathology. To investigate CBF changes common across psychiatric disorders, we capitalized upon a sample of 1042 youths (ages 11-23 years) who completed cross-sectional imaging as part of the Philadelphia Neurodevelopmental Cohort. CBF at rest was quantified on a voxelwise basis using arterial spin labeled perfusion MRI at 3T. A dimensional measure of psychopathology was constructed using a bifactor model of item-level data from a psychiatric screening interview, which delineated four factors (fear, anxious-misery, psychosis and behavioral symptoms) plus a general factor: overall psychopathology. Overall psychopathology was associated with elevated perfusion in several regions including the right dorsal anterior cingulate cortex (ACC) and left rostral ACC. Furthermore, several clusters were associated with specific dimensions of psychopathology. Psychosis symptoms were related to reduced perfusion in the left frontal operculum and insula, whereas fear symptoms were associated with less perfusion in the right occipital/fusiform gyrus and left subgenual ACC. Follow-up functional connectivity analyses using resting-state functional MRI collected in the same participants revealed that overall psychopathology was associated with decreased connectivity between the dorsal ACC and bilateral caudate. Together, the results of this study demonstrate common and dissociable CBF abnormalities across neuropsychiatric disorders in youth.
N-13 L-glutamate was used to image an osteogenic sarcoma in a 9-year-old patient. Serial quantitative measurements of the amount of N-13 taken up by the primary tumor showed a decrease of 40% after ...10 wk of chemotherapy. Blood-clearance data obtained from normal subjects indicate that more than 90% of the N-13 activity had left the blood before scanning of the tumor was begun. It appears that the N-13 label concentrated in the soft-tissue portion of this osteogenic sarcoma, whereas Tc-99m diphosphonate uptake was greatest in the regions where calcification was occurring.
Deep Learning for Ultrasonic Crack Characterization in NDE Pyle, Richard J.; Bevan, Rhodri L. T.; Hughes, Robert R. ...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control,
05/2021, Letnik:
68, Številka:
5
Journal Article
Recenzirano
Odprti dostop
Machine learning for nondestructive evaluation (NDE) has the potential to bring significant improvements in defect characterization accuracy due to its effectiveness in pattern recognition problems. ...However, the application of modern machine learning methods to NDE has been obstructed by the scarcity of real defect data to train on. This article demonstrates how an efficient, hybrid finite element (FE) and ray-based simulation can be used to train a convolutional neural network (CNN) to characterize real defects. To demonstrate this methodology, an inline pipe inspection application is considered. This uses four plane wave images from two arrays and is applied to the characterization of cracks of length 1-5 mm and inclined at angles of up to 20° from the vertical. A standard image-based sizing technique, the 6-dB drop method, is used as a comparison point. For the 6-dB drop method, the average absolute error in length and angle prediction is ±1.1 mm and ±8.6°, respectively, while the CNN is almost four times more accurate at ±0.29 mm and ±2.9°. To demonstrate the adaptability of the deep learning approach, an error in sound speed estimation is included in the training and test set. With a maximum error of 10% in shear and longitudinal sound speed, the 6-dB drop method has an average error of ±1.5 mmm and ±12°, while the CNN has ±0.45 mm and ±3.0°. This demonstrates far superior crack characterization accuracy by using deep learning rather than traditional image-based sizing.
Although self-report pain ratings are the gold standard in clinical pain assessment, they are inherently subjective in nature and significantly influenced by multidimensional contextual variables. ...Although objective biomarkers for pain could substantially aid pain diagnosis and development of novel therapies, reliable markers for clinical pain have been elusive. In this study, individualized physical maneuvers were used to exacerbate clinical pain in patients with chronic low back pain (N = 53), thereby experimentally producing lower and higher pain states. Multivariate machine-learning models were then built from brain imaging (resting-state blood-oxygenation-level-dependent and arterial spin labeling functional imaging) and autonomic activity (heart rate variability) features to predict within-patient clinical pain intensity states (ie, lower vs higher pain) and were then applied to predict between-patient clinical pain ratings with independent training and testing data sets. Within-patient classification between lower and higher clinical pain intensity states showed best performance (accuracy = 92.45%, area under the curve = 0.97) when all 3 multimodal parameters were combined. Between-patient prediction of clinical pain intensity using independent training and testing data sets also demonstrated significant prediction across pain ratings using the combined model (Pearson's r = 0.63). Classification of increased pain was weighted by elevated cerebral blood flow in the thalamus, and prefrontal and posterior cingulate cortices, and increased primary somatosensory connectivity to frontoinsular cortex. Our machine-learning approach introduces a model with putative biomarkers for clinical pain and multiple clinical applications alongside self-report, from pain assessment in noncommunicative patients to identification of objective pain endophenotypes that can be used in future longitudinal research aimed at discovery of new approaches to combat chronic pain.
Adenocarcinoma of bladder Malek, R S; Rosen, J S; O'Dea, M J
Urology (Ridgewood, N.J.)
21, Številka:
4
Journal Article
Recenzirano
Twenty-five patients with pure primary adenocarcinoma of the bladder were treated in a fifteen-year period. Practically all patients presented with some combination of gross hematuria, irritative ...lower urinary tract symptoms, or obstruction. Almost half the lesions were at the dome of the bladder. Most of the lesions were high grade and invasive. Transurethral resection is, at best, only diagnostic and palliative, and radiotherapy has been of little value. Radical cystectomy seems to produce five-year survival almost twice that of segmental resection. However, solitary lesions at the dome of the bladder, which usually represent neoplasia in a urachal remnant, seem to behave somewhat differently from lesions elsewhere in the bladder. Indeed, five-year survival of patients with lesions at the dome of the bladder who underwent segmental resection approximated that of those with similar lesions who underwent total cystectomy.
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