Utility of Kinetic, Dynamic, and Metabolic Data in Nonclinical Pharmacology/Toxicology Studies

1993 ◽  
pp. 15-22
Author(s):  
Judi Weissinger
Keyword(s):  
Metabolic Data

scholarly journals 243 Jugular Bulb Metabolic Data within First 12-Hours After Severe Head Trauma

1993 ◽  
Vol 8 (S3) ◽  
pp. S128-S129
Author(s):  
C.S De Deyne ◽  
J.M Decruyenaere ◽  
J.I Poelaert ◽  
F.A Colardyn
Keyword(s):  
Head Trauma ◽  
Jugular Bulb ◽  
Severe Head Trauma ◽  
Metabolic Data

BIOM-14. METABOLIC BIOMARKERS OF TERT-TARGETED THERAPY FOR HUMAN GLIOBLASTOMA DETECTED BY MAGNETIC RESONANCE SPECTROSCOPY

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi13-vi13
Author(s):  
Noriaki Minami ◽  
Donghyun Hong ◽  
Nicholas Stevers ◽  
Georgios Batsios ◽  
Anne Marie Gillespie ◽  
...  
Keyword(s):  
Targeted Therapy ◽  
1H Mrs ◽  
Significant Drop ◽  
Knock Down ◽  
Tert Promoter ◽  
Tert Promoter Mutations ◽  
Metabolic Data ◽  
Metabolic Biomarkers ◽  
Promoter Mutations ◽  
Tert Expression

Abstract BACKGROUND TERT promoter mutations that result in TERT expression are observed in over 80% of GBM. Moreover, the upstream transcription factor GABPB1 was recently identified as an ideal therapeutic target for tumors with TERT promoter mutations. In that context, non-invasive reliable biomarkers that can help detect TERT expression are needed. The aim of this research was to assess the value of MRS-detectable metabolic changes as biomarkers of TERT expression and TERT-targeted therapy in GBM. METHODS Genetically engineered GBM cells (NHARas/TERT) treated with TERT siRNA were compared to siCtrl-treated cells, and stable TERT and GABPB1 knock down GBM cells (U251, GBM1) were compared to shCtrl. 1H-MRS and 13C-MRS metabolic data was acquired from cell extracts using a Bruker 500MHz scanner. Hyperpolarized MRS studies of live cells used a HyperSense DNP polarizer and data was acquired using a Varian 500MHz scanner. Spectra were analyzed using Mnova and Matlab software. Multivariate data analysis was performed using SIMCA software. RESULTS Unbiased PCA analysis of 1H-MRS metabolic data showed separation of TERT or GABPB1 knock down and control cells. VIP predictive scores revealed that lactate and GSH were the top altered metabolites with a significant drop observed in both metabolites in every model following TERT silencing. Consistent with the reduction in GSH, spectrophotometric assays showed a significant drop in NADPH and NADH. 2-13C glucose flux analysis revealed that both glycolysis and PPP-related metabolites were reduced in TERT knock down cells. Hyperpolarized [1-13C]-pyruvate flux to lactate was also reduced, confirming that the glycolytic pathway was altered following TERT knock down. CONCLUSION 1H MRS-detectable lactate and GSH, combined with hyperpolarized 13C MRS-detectable metabolic fluxes, could serve as metabolic biomarkers of TERT-targeted therapy for human GBM with TERT promoter mutations. These biomarkers could be translated to the clinical, improve the monitoring of GBM patients and advance precision medicine.

Metabolic data for strontium

1979 ◽  
Vol 2 (3-4) ◽  
pp. 77-78 ◽  
Keyword(s):  
Metabolic Data

Taxonomic Use of Metabolic Data in Lichen-Forming Fungi

2020 ◽  
pp. 345-387
Author(s):  
Helge Thorsten Lumbsch
Keyword(s):  
Metabolic Data

Metabolic data for hydrogen

1979 ◽  
Vol 2 (3-4) ◽  
pp. 65-68 ◽  
Keyword(s):  
Metabolic Data

Pediatricians and Parents: Remarks on Receiving the C. Anderson Aldrich Award

PEDIATRICS ◽  
1977 ◽  
Vol 60 (4) ◽  
pp. 633-637
Author(s):  
Harry H. Gordon
Keyword(s):  
Infant Feeding ◽  
Ralph Waldo Emerson ◽  
Personality Development ◽  
Self Regulation ◽  
Young Infants ◽  
Metabolic Data ◽  
Metabolic Basis ◽  
Healthy Personality ◽  
Prematurely Born Infants

When John Bartram phoned to tell me of this greatly appreciated honor, he said I could speak to whatever topic I chose. Implicit in such trust was the assumption that I would be brief. Dr. Aldrich played a major role in bringing the practice of infant feeding from an era of pseudo-scientific misapplication of metabolic data into a psychologic era.1 He recognized that feeding was the the most important early transaction between mother and infant and that appropriate pediatric advice could promote healthy personality development. His wisdom was derived from a large experience with mothers and babies, and a grounding in the philosophic concepts of Ralph Waldo Emerson: "Respect the child. Be not too much his parent. . . . Respect the child, respect him to the end, but also respect yourself."2 I propose to address briefly the lack of respect by some pediatricians for the felt needs of mothers. Dr. Aldrich saw the mother and infant as a unit. He considered the term "self-demand" feeding too autocratic and substituted "self-regulation," recognizing that limits should be set which respected the mother and her other responsibilities as well as the infant. He preferred a schedule of feeding which was neither rigid, leading to anorexia, nor virtually nonexistent, leading to early obesity and what Spock termed chronic resistance to sleep, the latter a family affair with tensions for father as well as mother. His conceptualization led us to summarize our own laboratory observations under the title, "A Metabolic Basis for the Individualized Feeding of Young Infants," and to a later study of self-regulation of intake of food by prematurely born infants, a step toward flexible, sound advice to anxious mothers on discharge of their infants.3

Data Analysis and Presentation

2018 ◽  
pp. 177-192
Author(s):  
John R. B. Lighton
Keyword(s):  
Data Analysis ◽  
Temperature Effects ◽  
Final Analysis ◽  
Analysis Of Covariance ◽  
Neutral Zone ◽  
Metabolic Rates ◽  
Treatment Groups ◽  
Metabolic Data ◽  
Interspecific Comparisons ◽  
Selection Of

This chapter discusses ways of analyzing and presenting metabolic data while avoiding common mistakes. Topics covered include vital information often omitted from manuscripts; how to analyze the allometry of metabolic rate on mass; the mistake of reporting mass-specific or “mass-independent” metabolic rates; methods for quantifying differences between treatment groups by analysis of covariance; the importance of phylogeny in interspecific comparisons; the importance of the temperature at which measurements are made, including mammals (the thermal neutral zone); the necessity of leaving an “audit trail” from raw data through to final analysis; analyzing temperature effects such as Q10 correctly; and the proper selection of metabolic data.

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