Jason M. Ng
University of Pittsburgh
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Featured researches published by Jason M. Ng.
American Journal of Physiology-endocrinology and Metabolism | 2012
Jason M. Ng; Koichiro Azuma; Carol Kelley; R. Richard Pencek; Zofia Radiková; Charles M. Laymon; Julie C. Price; Bret H. Goodpaster; David E. Kelley
Excess amounts of abdominal subcutaneous (SAT) and visceral (VAT) adipose tissue (AT) are associated with insulin resistance, even in normal-weight subjects. In contrast, gluteal-femoral AT (GFAT) is hypothesized to offer protection against insulin resistance. Dynamic PET imaging studies were undertaken to examine the contributions of both metabolic activity and size (volume) of these depots in systemic glucose metabolism. Nonobese, healthy volunteers (n = 15) underwent dynamic PET imaging uptake of [¹⁸F]FDG at a steady-state (20 mU·m⁻²·min⁻¹) insulin infusion. PET images of tissue [¹⁸F]FDG activity were coregistered with MRI to derive K values for insulin-stimulated rates of fractional glucose uptake within tissue. Adipose tissue volume was calculated from DEXA and MRI. VAT had significantly higher rates of fractional glucose uptake per volume than SAT (P < 0.05) or GFAT (P < 0.01). K(GFAT) correlated positively (r = 0.67, P < 0.01) with systemic insulin sensitivity [glucose disappearance rate (R(d))] and negatively with insulin-suppressed FFA (r = -0.71, P < 0.01). SAT (r = -0.70, P < 0.01) and VAT mass (r = -0.55, P < 0.05) correlated negatively with R(d), but GFAT mass did not. We conclude that rates of fractional glucose uptake within GFAT and VAT are significantly and positively associated with systemic insulin sensitivity in nonobese subjects. Furthermore, whereas SAT and VAT amounts are confirmed to relate to systemic insulin resistance, GFAT amount is not associated with insulin resistance. These dynamic PET imaging studies indicate that both quantity and quality of specific AT depots have distinct roles in systemic insulin resistance and may help explain the metabolically obese but normal-weight phenotype.
Radiologic Clinics of North America | 2011
Tao Ouyang; William E. Rothfus; Jason M. Ng; Sue M. Challinor
In the appropriate clinical setting of pituitary hyperfunction or hypofunction, visual field deficit, or cranial nerve palsy, imaging of the pituitary is necessary. This article reviews the normal appearance of the pituitary and its surroundings, emphasizing magnetic resonance imaging. Typical and variant appearances of pituitary pathology are discussed. Because growth of adenoma into surrounding structures is important to surgical management, cavernous sinus invasion and suprasellar spread as well as adenoma mimics are illustrated. Typical examples of pituitary dysfunction from other entities that secondarily affect the gland, hypophysis, or third ventricle are discussed. Some common errors of interpretation are listed.
Diabetes | 2014
Bret H. Goodpaster; Alessandra Bertoldo; Jason M. Ng; Koichiro Azuma; R. Richard Pencek; Carol Kelley; Julie C. Price; Claudio Cobelli; David E. Kelley
Dynamic positron emission tomography (PET) imaging was performed using sequential tracer injections ([15O]H2O, [11C]3-O-methylglucose [3-OMG], and [18F]fluorodeoxyglucose [FDG]) to quantify, respectively, skeletal muscle tissue perfusion (glucose delivery), kinetics of bidirectional glucose transport, and glucose phosphorylation to interrogate the individual contribution and interaction among these steps in muscle insulin resistance (IR) in type 2 diabetes (T2D). PET imaging was performed in normal weight nondiabetic subjects (NW) (n = 5), obese nondiabetic subjects (OB) (n = 6), and obese subjects with T2D (n = 7) during fasting conditions and separately during a 6-h euglycemic insulin infusion at 40 mU·m−2·min−1. Tissue tracer activities were derived specifically within the soleus muscle with PET images and magnetic resonance imaging. During fasting, NW, OB, and T2D subjects had similar [11C]3-OMG and [18F]FDG uptake despite group differences for tissue perfusion. During insulin-stimulated conditions, IR was clearly evident in T2D (P < 0.01), and [18F]FDG uptake by muscle was inversely correlated with systemic IR (P < 0.001). The increase in insulin-stimulated glucose transport was less (P < 0.01) in T2D (twofold) than in NW (sevenfold) or OB (sixfold) subjects. The fractional phosphorylation of [18F]FDG during insulin infusion was also significantly lower in T2D (P < 0.01). Dynamic triple-tracer PET imaging indicates that skeletal muscle IR in T2D involves a severe impairment of glucose transport and additional impairment in the efficiency of glucose phosphorylation.
The Journal of Clinical Endocrinology and Metabolism | 2014
Jason M. Ng; Alessandra Bertoldo; Davneet Minhas; Nicole L. Helbling; Paul M. Coen; Julie C. Price; Claudio Cobelli; David E. Kelley; Bret H. Goodpaster
PURPOSE Skeletal muscle insulin resistance (IR) often precedes hyperglycemia and type 2 diabetes. However, variability exists within different skeletal muscle types and can be influenced by 3 primary steps of control: glucose delivery, transport, and phosphorylation. We performed dynamic positron emission tomography imaging studies to determine the extent to which heterogeneity in muscle type and control of insulin action contribute to IR. METHODS Thirteen volunteers from normal weight to obese underwent dynamic positron emission tomography imaging of [15O]H2O, [11C]3-O-methylglucose, and [18F]fluorodeoxyglucose, measuring delivery, transport, and phosphorylation rates, respectively, in soleus and tibialis anterior muscle during a hyperinsulinemic-euglycemic clamp. Subjects were classified as insulin-sensitive (IS) or insulin-resistant (IR) based on the median systemic glucose infusion rate needed to maintain euglycemia. RESULTS In soleus, transport kinetic rates were significantly higher (P<.05) in IS (0.126±0.028 min(-1)) vs IR (0.051±0.008 min(-1)) subjects. These differences were not as evident in tibialis anterior. These differences were paralleled in overall insulin-stimulated tissue activity, higher in IS (0.017±0.001 mL·cm3·min(-1)) vs IR (0.011±0.002 mL·cm3·min(-1)) in soleus (P<.05), without significant differences in tibialis anterior. No significant differences were observed for either muscle in delivery or phosphorylation. Both muscle types displayed a control shift from an even distribution among the steps in IS to transport exerting greater control of systemic insulin sensitivity in IR. CONCLUSION Lower glucose transport rates are the major feature underlying IR preceding type 2 diabetes, although substantial heterogeneity in insulin action across muscle types highlight the complexity of skeletal muscle IR.
Current Opinion in Clinical Nutrition and Metabolic Care | 2009
Jason M. Ng; David E. Kelley; Bret H. Goodpaster
Purpose of reviewSkeletal muscle insulin resistance is a hallmark characteristic of type 2 diabetes, although the exact causes of insulin resistance are unknown. In-vivo methods to assess mechanisms that determine insulin resistance in humans are critical to improve our understanding of insulin resistance in obesity and type 2 diabetes. In this review, we examine recent studies utilizing dynamic in-vivo PET imaging in assessing insulin resistance in humans. Recent findingsPET imaging of glucose metabolism in vivo has revealed novel and important information about the regulation of glucose metabolism in skeletal muscle. Using dynamic PET imaging, studies have impairments in glucose metabolism at multiple sites, including delivery, phosphorylation, and transport within skeletal muscle. Impairments in glucose phosphorylation as well as glucose transport defects may play an important role in understanding the disorder of skeletal muscle insulin resistance. SummaryPET imaging has great potential to yield significant and promising insight into insulin resistance in skeletal muscle. Dynamic in-vivo PET imaging can provide valuable information regarding the mechanisms and specific loci of skeletal muscle insulin resistance in humans.
BMJ open diabetes research & care | 2017
Simona Ioja; Eileen R. Chasens; Jason M. Ng; Patrick J. Strollo; Mary T. Korytkowski
Objective Obstructive sleep apnea (OSA) and diabetes are frequent comorbid conditions. Screening for OSA in patients with diabetes is recommended but the frequency with which this is done in clinical practice is unknown. The objectives of this quality improvement initiative were to identify clinician and patient perceptions regarding OSA and to identify the prevalence of patients at high risk for OSA (HROSA). Methods A quality improvement initiative was conducted to query clinicians and patients attending a specialty diabetes clinic regarding attitudes and beliefs related to OSA. The Berlin Questionnaire was embedded in patient questionnaires to identify patients as low risk for OSA (LROSA) or HROSA. Results 35 clinicians completed questionnaires with >80% agreement that OSA contributed to blood pressure (BP), glycemic control, and diabetes complications and that screening is a shared responsibility with other physicians; but only 17% indicated regular screening due predominantly to insufficient time. Of 107 patients (26 type 1 diabetes mellitus (T1DM) and 81 type 2 diabetes mellitus (T2DM)), 30% were aware that OSA could affect diabetes outcomes. The prevalence of known OSA, LROSA, and HROSA was similar in T1DM (15%, 50%, 35%) and T2DM (36%, 33%, 31%, respectively) (p=0.21). 59% of all HROSA patients indicated that OSA screening had never been discussed with them. Conclusions These results demonstrate that providers, but not patients, are knowledgeable about the importance of OSA screening, but insufficient time is a major barrier to wider screening. Approximately, 30% of patients with T1DM and T2DM were identified as HROSA supporting the need for procedures that improve detection and treatment.
World Neurosurgery | 2017
Samuel S. Shin; Paul A. Gardner; Jason M. Ng; Amir H. Faraji; Nitin Agarwal; Srinivas Chivukula; Juan C. Fernandez-Miranda; Carl H. Snyderman; Sue M. Challinor
World Neurosurgery | 2015
Samuel S. Shin; Paul A. Gardner; Jason M. Ng; Amir H. Faraji; Nitin Agarwal; Srinivas Chivukula; Juan C. Fernandez-Miranda; Carl H. Snyderman; Sue M. Challinor
/data/revues/00338389/v49i3/S0033838911000315/ | 2011
Tao Ouyang; William E. Rothfus; Jason M. Ng; Sue M. Challinor
Journal of diabetes science and technology | 2018
Dinesh Edem; Patrick McCarthy; Jason M. Ng; Maja Stefanovic-Racic; Mary T. Korytkowski