1.In Vivo and In Vitro Quantification of Glucose Kinetics: From Bedside to Bench
Il-Young KIM ; Sanghee PARK ; Yeongmin KIM ; Yewon CHANG ; Cheol Soo CHOI ; Sang-Hoon SUH ; Robert R. WOLFE
Endocrinology and Metabolism 2020;35(4):733-749
Like other substrates, plasma glucose is in a dynamic state of constant turnover (i.e., rates of glucose appearance [Ra glucose] into and disappearance [Rd glucose] from the plasma) while staying within a narrow range of normal concentrations, a physiological priority. Persistent imbalance of glucose turnover leads to elevations (i.e., hyperglycemia, Ra>Rd) or falls (i.e., hypoglycemia, Ra
2.Quantifications of Lipid Kinetics In Vivo Using Stable Isotope Tracer Methodology
Il Young KIM ; Sanghee PARK ; Jiwoong JANG ; Robert R WOLFE
Journal of Lipid and Atherosclerosis 2020;9(1):110-123
Like other bodily materials, lipids such as plasma triacylglycerol, cholesterols, and free fatty acids are in a dynamic state of constant turnover (i.e., synthesis, breakdown, oxidation, and/or conversion to other compounds) as essential processes for achieving dynamic homeostasis in the body. However, dysregulation of lipid turnover can lead to clinical conditions such as obesity, fatty liver disease, and dyslipidemia. Assessment of “snap-shot†information on lipid metabolism (e.g., tissue contents of lipids, abundance of mRNA and protein and/or signaling molecules) are often used in clinical and research settings, and can help to understand one's health and disease status. However, such “snapshots†do not provide critical information on dynamic nature of lipid metabolism, and therefore may miss “true†origin of the dysregulation implicated in related diseases. In this regard, stable isotope tracer methodology can provide the in vivo kinetic information of lipid metabolism. Combining with “static†information, knowledge of lipid kinetics can enable the acquisition of in depth understanding of lipid metabolism in relation to various health and disease status. This in turn facilitates the development of effective therapeutic approaches (e.g., exercise, nutrition, and/or drugs). In this review we will discuss 1) the importance of obtaining kinetic information for a better understanding of lipid metabolism, 2) basic principles of stable isotope tracer methodologies that enable exploration of “lipid kinetics†in vivo, and 3) quantification of some aspects of lipid kinetics in vivo with numerical examples.
3.Applications of stable, nonradioactive isotope tracers in in vivo human metabolic research.
Il Young KIM ; Sang Hoon SUH ; In Kyu LEE ; Robert R WOLFE
Experimental & Molecular Medicine 2016;48(1):e203-
The human body is in a constant state of turnover, that is, being synthesized, broken down and/or converted to different compounds. The dynamic nature of in vivo kinetics of human metabolism at rest and in stressed conditions such as exercise and pathophysiological conditions such as diabetes and cancer can be quantitatively assessed with stable, nonradioactive isotope tracers in conjunction with gas or liquid chromatography mass spectrometry and modeling. Although measurements of metabolite concentrations have been useful as general indicators of one's health status, critical information on in vivo kinetics of metabolites such as rates of production, appearance or disappearance of metabolites are not provided. Over the past decades, stable, nonradioactive isotope tracers have been used to provide information on dynamics of specific metabolites. Stable isotope tracers can be used in conjunction with molecular and cellular biology tools, thereby providing an in-depth dynamic assessment of metabolic changes, as well as simultaneous investigation of the molecular basis for the observed kinetic responses. In this review, we will introduce basic principles of stable isotope methodology for tracing in vivo kinetics of human or animal metabolism with examples of quantifying certain aspects of in vivo kinetics of carbohydrate, lipid and protein metabolism.
Animals
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Chromatography, Liquid
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Human Body
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Humans*
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Kinetics
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Mass Spectrometry
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Metabolism
4.Thrombectomy in Stroke Patients With Low Alberta Stroke Program Early Computed Tomography Score: Is Modified Thrombolysis in Cerebral Infarction (mTICI) 2c/3 Superior to mTICI 2b?
Sameh Samir ELAWADY ; Brian Fabian SAWAY ; Hidetoshi MATSUKAWA ; Kazutaka UCHIDA ; Steven LIN ; Ilko MAIER ; Pascal JABBOUR ; Joon-Tae KIM ; Stacey Quintero WOLFE ; Ansaar RAI ; Robert M. STARKE ; Marios-Nikos PSYCHOGIOS ; Edgar A SAMANIEGO ; Adam ARTHUR ; Shinichi YOSHIMURA ; Hugo CUELLAR ; Jonathan A. GROSSBERG ; Ali ALAWIEH ; Daniele G. ROMANO ; Omar TANWEER ; Justin MASCITELLI ; Isabel FRAGATA ; Adam POLIFKA ; Joshua OSBUN ; Roberto CROSA ; Charles MATOUK ; Min S. PARK ; Michael R. LEVITT ; Waleed BRINJIKJI ; Mark MOSS ; Travis DUMONT ; Richard WILLIAMSON JR. ; Pedro NAVIA ; Peter KAN ; Reade De LEACY ; Shakeel CHOWDHRY ; Mohamad EZZELDIN ; Alejandro M. SPIOTTA ; Sami Al KASAB ;
Journal of Stroke 2024;26(1):95-103
Background:
and Purpose Outcomes following mechanical thrombectomy (MT) are strongly correlated with successful recanalization, traditionally defined as modified Thrombolysis in Cerebral Infarction (mTICI) ≥2b. This retrospective cohort study aimed to compare the outcomes of patients with low Alberta Stroke Program Early Computed Tomography Score (ASPECTS; 2–5) who achieved mTICI 2b versus those who achieved mTICI 2c/3 after MT.
Methods:
This study utilized data from the Stroke Thrombectomy and Aneurysm Registry (STAR), which combined databases from 32 thrombectomy-capable stroke centers between 2013 and 2023. The study included only patients with low ASPECTS who achieved mTICI 2b, 2c, or 3 after MT for internal carotid artery or middle cerebral artery (M1) stroke.
Results:
Of the 10,229 patients who underwent MT, 234 met the inclusion criteria. Of those, 98 (41.9%) achieved mTICI 2b, and 136 (58.1%) achieved mTICI 2c/3. There were no significant differences in baseline characteristics between the two groups. The 90-day favorable outcome (modified Rankin Scale score: 0–3) was significantly better in the mTICI 2c/3 group than in the mTICI 2b group (adjusted odds ratio 2.35; 95% confidence interval [CI] 1.18–4.81; P=0.02). Binomial logistic regression revealed that achieving mTICI 2c/3 was significantly associated with higher odds of a favorable 90-day outcome (odds ratio 2.14; 95% CI 1.07–4.41; P=0.04).
Conclusion
In patients with low ASPECTS, achieving an mTICI 2c/3 score after MT is associated with a more favorable 90-day outcome. These findings suggest that mTICI 2c/3 is a better target for MT than mTICI 2b in patients with low ASPECTS.