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Record W36505075 · doi:10.3389/fphys.2022.1009320

Defisit anggaran, utang pemerintah dan keberlanjutan fiscal: aplikasi model vector error correction

2005· article· en· W36505075 on OpenAlexfundno aff
Bambang Subagjo

Bibliographic record

VenueFrontiers in Physiology · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer science

Abstract

fetched live from OpenAlex

<i>p</i>-Tyramine (TYR) is an endogenous trace amine, which can also be synthesized by intestinal microbiota, and is present in commonly consumed diets. TYR is an agonist for the intracellular trace amine-associated receptor 1, which has been implicated in psychiatric, metabolic, and immune-related disorders. We have previously demonstrated TYR readily diffuses across lipid bilayers, while transport across Caco-2 cell membranes involves Organic Cation Transporter 2 (OCT2) and a Na<sup>+</sup>-dependent active transporter. Here we developed mathematical models to determine whether known kinetics for these processes are sufficient to explain observed transcellular TYR passage. Ordinary differential equations were developed for known TYR transport processes to predict concentration-time relationships. Michaelis-Menten kinetics were assumed for all transporter-mediated processes and a one phase exponential function used for simple diffusion. Modelled concentration-time plots were compared to published experimental results. Additional transporter functions were sequentially added to models to improve consistency, and a least squares error minimization approach utilized to determine added transporter kinetics. Finally, possible TYR compartmentalization was also modelled. Following apical loading, transport across the apical, but not the basolateral, membrane was modelled without additional transporters, suggesting a basolateral transporter was missing. Consistent with this, models of basolateral compartment loading did not match experimental observations, indicating missing basolateral transporters were bidirectional. Addition of a transporter with the kinetic characteristics of OCT2 did not improve models. Varying the kinetic parameters of the added transporter improved models of basolateral, but worsened apical, loading models, suggesting the need for either a directional preference in transporters, or intracellular TYR compartmentalization. Experimental parameters were recapitulated by introducing asymmetry into the apical OCT2 (K<sub>t_OCT2_apicaltocell</sub> = 110.4 nM, K<sub>t_OCT2_celltoapical</sub> = 1,227.9 nM), and a symmetric basolateral facilitated diffusion transporter (V<sub>max</sub> = 6.0 nM/s, K<sub>t</sub> = 628.3 nM). The apparent directionality of OCT2 may reflect altered TYR ionization due to known pH differences between compartments. Models for asymmetry and compartmentalization were compared by root mean square deviation from experimental data, and it was found that TYR compartmentalization could only partially replace the need for asymmetry of OCT2. In conclusion, modelling indicates that known TYR transport processes are insufficient to explain experimental concentration-time profiles and that asymmetry of the apical membrane OCT2 combined with additional, low affinity, basolateral membrane facilitated diffusion transporters are required.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.216
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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