A novel mutation of the ACADM gene (c.145C>G) associated with the common c.985A>G mutation on the other ACADM allele causes mild MCAD deficiency: a case report.

A female patient, with normal familial history, developed at the age of 30 months an episode of diarrhoea, vomiting and lethargy which resolved spontaneously. At the age of 3 years, the patient re-iterated vomiting, was sub-febrile and hypoglycemic, fell into coma, developed seizures and sequels involving right hemi-body. Urinary excretion of hexanoylglycine and suberylglycine was low during this metabolic decompensation. A study of pre- and post-prandial blood glucose and ketones over a period of 24 hours showed a normal glycaemic cycle but a failure to form ketones after 12 hours fasting, suggesting a mitochondrial β-oxidation defect. Total blood carnitine was lowered with unesterified carnitine being half of the lowest control value. A diagnosis of mild MCAD deficiency (MCADD) was based on rates of 1-14C-octanoate and 9, 10-3H-myristate oxidation and of octanoyl-CoA dehydrogenase being reduced to 25% of control values. Other mitochondrial fatty acid oxidation proteins were functionally normal. De novo acylcarnitine synthesis in whole blood samples incubated with deuterated palmitate was also typical of MCADD. Genetic studies showed that the patient was compound heterozygous with a sequence variation in both of the two ACADM alleles; one had the common c.985A>G mutation and the other had a novel c.145C>G mutation. This is the first report for the ACADM gene c.145C>G mutation: it is located in exon 3 and causes a replacement of glutamine to glutamate at position 24 of the mature protein (Q24E). Associated with heterozygosity for c.985A>G mutation, this mutation is responsible for a mild MCADD phenotype along with a clinical story corroborating the emerging literature view that patients with genotypes representing mild MCADD (high residual enzyme activity and low urinary levels of glycine conjugates), similar to some of the mild MCADDs detected by MS/MS newborn screening, may be at risk for disease presentation.

PDLA a potential new potent topical analgesic: a case report.

Polymer D-lactic acid (PDLA) is a hydrogel that has been shown to sequester L-lactate (lactate). This reaction is rapid, spontaneous, and non-enzymatic. Lactate has been shown to have many functions within the nervous system including its use as a secondary fuel to sustain neural activity and as a neuromodulator. In the central nervous system, lactate is produced in glial cells and shuttled to neurons to be used mostly as a fuel. Lactate dehydrogenase (LDH)1 is the predominant LDH isoform within neurons and unlike LDH5, it preferentially converts lactate to pyruvate which can be used to produce adenosine triphosphate (ATP). Considering that lactate is intimately involved in the sustenance of neural activity, PDLA was applied to an open wound and its effects were examined. The results showed that the application of PDLA induced topical analgesia. This may be the first report to demonstrate that sequestering lactate, a source of energy required to sustain the firing of action potentials in neurons, may produce analgesia.

Quantifying data quality for clinical trials using electronic data capture.

BACKGROUND: Historically, only partial assessments of data quality have been performed in clinical trials, for which the most common method of measuring database error rates has been to compare the case report form (CRF) to database entries and count discrepancies. Importantly, errors arising from medical record abstraction and transcription are rarely evaluated as part of such quality assessments. Electronic Data Capture (EDC) technology has had a further impact, as paper CRFs typically leveraged for quality measurement are not used in EDC processes. METHODS AND PRINCIPAL FINDINGS: The National Institute on Drug Abuse Treatment Clinical Trials Network has developed, implemented, and evaluated methodology for holistically assessing data quality on EDC trials. We characterize the average source-to-database error rate (14.3 errors per 10,000 fields) for the first year of use of the new evaluation method. This error rate was significantly lower than the average of published error rates for source-to-database audits, and was similar to CRF-to-database error rates reported in the published literature. We attribute this largely to an absence of medical record abstraction on the trials we examined, and to an outpatient setting characterized by less acute patient conditions. CONCLUSIONS: Historically, medical record abstraction is the most significant source of error by an order of magnitude, and should be measured and managed during the course of clinical trials. Source-to-database error rates are highly dependent on the amount of structured data collection in the clinical setting and on the complexity of the medical record, dependencies that should be considered when developing data quality benchmarks.