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Abstract Objective The use of folic acid (FA) has been discouraged in cerebral folate deficiency (CFD) because, theoretically, it could inhibit the transport of 5‐methyltetrahydrofolic acid (5MTHF) across the blood–cerebrospinal fluid (CSF) barrier. We present the clinical biochemical data of two cases with CFD to support this hypothesis. Methods We measured CSF and serum 5MTHF concentrations in a patient with Kearns‐Sayre syndrome (KSS) and a patient homozygous for MTHFR C677T polymorphism before and during folate supplementation therapy. To evaluate these 5MTHF concentrations, we also analyzed CSF and serum samples in pediatric patients without folate supplementation. Results Both patients had low CSF 5MTHF before treatment and high‐dose FA therapy did not normalize CSF 5MTHF. There was a dissociation between serum total folate and 5MTHF concentrations during FA therapy, which was considered to be due to the appearance of unmetabolized FA. The addition of folinic acid did not improve low CSF 5MTHF in the KSS patient and the cessation of FA resulted in the normalization of CSF 5MTHF. In the patient homozygous for MTHFR C677T, minimization of the FA dosage resulted in the normalization of CSF 5MTHF and an increased CSF‐to‐serum 5MTHF ratio. Conclusions Our data suggest that excess supplementation of FA impaired 5MTHF transport across the blood–CSF barrier. In the treatment of CFD, supplementation of folinic acid or 5MTHF (in cases of impaired 5MTHF synthesis) is preferred over the use of FA. The reference values of CSF 5MTHF concentration based on 600 pediatric cases were also provided.

Abstract These days, networked control systems (NCSs) in which data is transmitted via communication have been actively studied for many potential applications. In an NCS, data dropout degrades control performance depending on network conditions. For an NCS with data dropout, the authors propose a model‐predictive‐control‐based input optimisation, representing data dropout as both a Bernoulli model and a finite‐order Markov chain. Using the proposed NCS data dropout model, the authors derive an optimal input that provides the estimated error between the expected state of the plant and a given reference. The proposed control problem is formulated as its equivalent quadratic programming, as executed at each online sampling. The authors also demonstrate simulations and experiments to show the effectiveness of the proposed method.