Cálcio ionizado no soro: estimativa do intervalo de referência e condições de coleta

Andriolo, Adagmar; Moreira, Silvia; Silva, Luciene Alves; Carvalho, Aluízio Barbosa de; Vieira, José Gilberto H.; Ghiringhello, Maria Teresa; Juliano, Yára

doi:10.1590/s1676-24442004000200007

Cited by 5 publications

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“…The concentration of these compounds complexed as ion-ligand(s) or in their free state is controlled by the pH, temperature, ionic strength and concentration of other metal ions (1). The equilibrium between these metal ions and their ligands is important to allow the biological system to work properly.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the applicability of artificial neural networks for studying blood plasma: determination of magnesium ion concentration as a case study

Liparini

Carvalho²,

Belchior

2005

Clinical Chemistry and Laboratory Medicine (CCLM)

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Artificial neural networks are suggested for use in predicting metal ion concentration in human blood plasma. Simulated and available experimental data are used to train the artificial neural network. Particularly, using 850 simulated samples, the network predicted the magnesium-free ion concentration with an average error smaller than 1%. Clinical data recently reported for 20 patients were considered and the artificial neural network predicted the concentration of free magnesium ion with an average error of about 6%. Overall, the approach of using artificial neural networks as an alternative or complementary strategy to deal with the analysis of human blood plasma can be useful for clinical diagnostics, if there is sufficient data to train the artificial neural network.

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Section: Introductionmentioning

confidence: 99%

Analysis of the applicability of artificial neural networks for studying blood plasma: determination of magnesium ion concentration as a case study

Liparini

Carvalho²,

Belchior

2005

Clinical Chemistry and Laboratory Medicine (CCLM)

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Analyses of the temperature and pH effects on the complexation of magnesium and calcium in human blood plasma: an approach using artificial neural networks

et al. 2007

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The temperature and pH effects on the equilibrium of a blood plasma model have been studied on the basis of artificial neural networks. The proposed blood plasma was modeled considering two important metals, calcium and magnesium, and six ligands, namely, alanate, carbonate, citrate, glycinate, histidinate and succinate. A large data set has been used to simulate different concentrations of magnesium and calcium as a function of temperature and pH and these data were used for training the neural network. The proposed model allowed different types of analyses, such as the effects of pH on calcium and magnesium concentrations, the competition between calcium and magnesium for ligands and the effects of temperature on calcium and magnesium concentrations. The model developed was also used to predict how the variation of calcium concentration can affect magnesium concentrations. A comparison of neural network predictions against experimental data produced errors of about 3%. Moreover, in agreement with experimental measurements (Wang et al. in Arch. Pathol. 126:947-950, 2002; Heining et al. in Scand. J. Clin. Lab. Invest. 43:709-714, 1983), the artificial neural network predicted that calcium and magnesium concentrations decrease when pH increases. Similarly, the magnesium concentrations are less sensitive than calcium concentrations to pH changes. It is also found that both calcium and magnesium concentrations decrease when the temperature increases. Finally, the theoretical model also predicted that an increase of calcium concentrations will lead to an increase of magnesium concentration almost at the same rate. These results suggest that artificial neural networks can be efficiently applied as a complementary tool for studying metal ion complexation, with especial attention to the blood plasma analysis.

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Vitamin D and its relation with ionic calcium, parathyroid hormone, maternal and neonatal characteristics in pregnancy after roux-en-Y gastric bypass

Medeiros

Matos

Pereira

et al. 2015

Arch Gynecol Obstet

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Cálcio ionizado no soro: estimativa do intervalo de referência e condições de coleta

Cited by 5 publications

References 0 publications

Analysis of the applicability of artificial neural networks for studying blood plasma: determination of magnesium ion concentration as a case study

Analysis of the applicability of artificial neural networks for studying blood plasma: determination of magnesium ion concentration as a case study

Analyses of the temperature and pH effects on the complexation of magnesium and calcium in human blood plasma: an approach using artificial neural networks

Vitamin D and its relation with ionic calcium, parathyroid hormone, maternal and neonatal characteristics in pregnancy after roux-en-Y gastric bypass

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