Mathematical modeling and parameter estimation of levodopa motor response in patients with Parkinson disease

Parkinson disease (PD) is characterized by a clear beneficial motor response to levodopa (LD) treatment. However, with disease progression and longer LD exposure, drug-related motor fluctuations usually occur. Recognition of the individual relationship between LD concentration and its effect may be difficult, due to the complexity and variability of the mechanisms involved. This work proposes an innovative procedure for the automatic estimation of LD pharmacokinetics and pharmacodynamics parameters, by a biologically-inspired mathematical model. An original issue, compared with previous similar studies, is that the model comprises not only a compartmental description of LD pharmacokinetics in plasma and its effect on the striatal neurons, but also a neurocomputational model of basal ganglia action selection. Parameter estimation was achieved on 26 patients (13 with stable and 13 with fluctuating LD response) to mimic plasma LD concentration and alternate finger tapping frequency along four hours after LD administration, automatically minimizing a cost function of the difference between simulated and clinical data points. Results show that individual data can be satisfactorily simulated in all patients and that significant differences exist in the estimated parameters between the two groups. Specifically, the drug removal rate from the effect compartment, and the Hill coefficient of the concentration-effect relationship were significantly higher in the fluctuating than in the stable group. The model, with individualized parameters, may be used to reach a deeper comprehension of the PD mechanisms, mimic the effect of medication, and, based on the predicted neural responses, plan the correct management and design innovative therapeutic procedures

Probability amplitude in quantum like games

Examples of games between two partners with mixed strategies, calculated by the use of the probability amplitude are given. The first game is described by the quantum formalism of spin one half system for which two noncommuting observables are measured. The second game corresponds to the spin one case. Quantum logical orthocomplemented nondistributive lattices for these two games are presented. Interference terms for the probability amplitudes are analyzed by using so called contextual approach to probability (in the von Mises frequency approach). We underline that our games are not based on using of some microscopic systems. The whole scenario is macroscopic.Comment: Quantum-like model

Caracterização socioeconômica das bacias hidrográficas dos Rios Guapi-Macacu e Caceribu.

bitstream/item/107015/1/DOC-149-Socioeconomia-Guapi-Macacu.pd

Quantitative Assessment of Motor Response to a Low Subacute Levodopa Dose in the Differential Diagnosis of Parkinsonisms at Disease Onset: Data from the BoProPark Cohort

Background: Differential diagnosis between Parkinson's disease (PD) and atypical parkinsonisms (APs) may be difficult at disease onset. The response to levodopa (LD) is a key supportive feature but its definition is largely empirical. Studies evaluating this issue by quantitative tests are scanty. Objective: We aimed to assess the utility of a subacute low LD dose kinetic-dynamic test in the differential diagnosis between PD and APs. It was applied at the baseline of a prospective follow-up in patients with parkinsonian signs within three years of disease motor onset ('BoProPark' cohort) and eventually diagnosed as PD or APs according to consensus criteria. Methods: Patients under at least 3-month LD therapy received a first morning fasting dose of LD/benserazide or carbidopa (100/25mg) and underwent simultaneous serial assessments of plasma LD concentration and alternate finger tapping frequency up to 3h. The main outcome was the extent of LD motor response, calculated by the area under the 3h tapping effect-time curve (AUC_ETap). A receiver operating characteristic (ROC) curve analysis was performed to establish the optimal AUC_ETap cut-off to differentiate PD and APs. Results: The first 100 consecutive 'BoProPark' patients were analyzed. Forty-seven patients were classified as possible, 37 as probable PD and 16 as APs. AUC_ETap medians were similar in the PD subgroups but reduced to a third in APs (p<0.001). The optimal AUC_ETap cut-off value was >2186 [(tap/min) x min], with a sensitivity of 92% and a specificity of 75%. Accuracy of the test was 0.85 (95% CI 0.74-0.95), p<0.0001. Conclusion: The estimation of 3h AUC_ETap after a subacute low LD dose proved a reliable, objective tool to assess LD motor response in our cohort of patients. AUC_ETap value rounded to ≥2200 supports PD diagnosis, while lower values may alert to AP diagnoses