Aerosolized amikacin for treatment of pulmonary Mycobacterium avium infections: an observational case series

BACKGROUND: Current systemic therapy for nontuberculous mycobacterial pulmonary infection is limited by poor clinical response rates, drug toxicities and side effects. The addition of aerosolized amikacin to standard oral therapy for nontuberculous mycobacterial pulmonary infection may improve treatment efficacy without producing systemic toxicity. This study was undertaken to assess the safety, tolerability and preliminary clinical benefits of the addition of aerosolized amikacin to a standard macrolide-based oral treatment regimen. CASE PRESENTATIONS: Six HIV-negative patients with Mycobacterium avium intracellulare pulmonary infections who had failed standard therapy were administered aerosolized amikacin at 15 mg/kg daily in addition to standard multi-drug macrolide-based oral therapy. Patients were monitored clinically and serial sputum cultures were obtained to assess response to therapy. Symptomatic improvement with radiographic stabilization and eradication of mycobacterium from sputum were considered markers of success. Of the six patients treated with daily aerosolized amikacin, five responded to therapy. All of the responders achieved symptomatic improvement and four were sputum culture negative after 6 months of therapy. Two patients became re-infected with Mycobacterium avium intracellulare after 7 and 21 months of treatment. One of the responders who was initially diagnosed with Mycobacterium avium intracellulare became sputum culture positive for Mycobacterium chelonae resistant to amikacin after being on intermittent therapy for 4 years. One patient had progressive respiratory failure and died despite additional therapy. There was no evidence of nephrotoxicity or ototoxicity associated with therapy. CONCLUSION: Aerosolized delivery of amikacin is a promising adjunct to standard therapy for pulmonary nontuberculous mycobacterial infections. Larger prospective trials are needed to define its optimal role in therapy of this disease

A combination of ascorbic acid and α-tocopherol to test the effectiveness and safety in the fragile X syndrome: study protocol for a phase II, randomized, placebo-controlled trial

BACKGROUND: Fragile X syndrome (FXS) is an inherited neurodevelopmental condition characterised by behavioural, learning disabilities, phisical and neurological symptoms. In addition, an important degree of comorbidity with autism is also present. Considered a rare disorder affecting both genders, it first becomes apparent during childhood with displays of language delay and behavioural symptoms. Main aim: To show whether the combination of 10 mg/kg/day of ascorbic acid (vitamin C) and 10 mg/kg/day of α-tocopherol (vitamin E) reduces FXS symptoms among male patients ages 6 to 18 years compared to placebo treatment, as measured on the standardized rating scales at baseline, and after 12 and 24 weeks of treatment. Secondary aims: To assess the safety of the treatment. To describe behavioural and cognitive changes revealed by the Developmental Behaviour Checklist Short Form (DBC-P24) and the Wechsler Intelligence Scale for Children–Revised. To describe metabolic changes revealed by blood analysis. To measure treatment impact at home and in an academic environment. METHODS/DESIGN: A phase II randomized, double-blind pilot clinical trial. Scope: male children and adolescents diagnosed with FXS, in accordance with a standardized molecular biology test, who met all the inclusion criteria and none of the exclusion criteria. Instrumentation: clinical data, blood analysis, Wechsler Intelligence Scale for Children–Revised, Conners parent and teacher rating scale scores and the DBC-P24 results will be obtained at the baseline (t0). Follow up examinations will take place at 12 weeks (t1) and 24 weeks (t2) of treatment. DISCUSSION: A limited number of clinical trials have been carried out on children with FXS, but more are necessary as current treatment possibilities are insufficient and often provoke side effects. In the present study, we sought to overcome possible methodological problems by conducting a phase II pilot study in order to calculate the relevant statistical parameters and determine the safety of the proposed treatment. The results will provide evidence to improve hyperactivity control and reduce behavioural and learning problems using ascorbic acid (vitamin C) and α-tocopherol (vitamin E). The study protocol was approved by the Regional Government Committee for Clinical Trials in Andalusia and the Spanish agency for drugs and health products. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01329770 (29 March 2011

A white paper on a neurodevelopmental framework for drug discovery in autism and other neurodevelopmental disorders

In the last decade there has been a revolution in terms of genetic findings in neurodevelopmental disorders (NDDs), with many discoveries critical for understanding their aetiology and pathophysiology. Clinical trials in single-gene disorders such as fragile X syndrome highlight the challenges of investigating new drug targets in NDDs. Incorporating a developmental perspective into the process of drug development for NDDs could help to overcome some of the current difficulties in identifying and testing new treatments. This paper provides a summary of the proceedings of the ‘New Frontiers Meeting’ on neurodevelopmental disorders organised by the European College of Neuropsychopharmacology in conjunction with the Innovative Medicines Initiative-sponsored AIMS-2-TRIALS consortium. It brought together experts in developmental genetics, autism, NDDs, and clinical trials from academia and industry, regulators, patient and family associations, and other stakeholders. The meeting sought to provide a platform for focused communication on scientific insights, challenges, and methodologies that might be applicable to the development of CNS treatments from a neurodevelopmental perspective. Multidisciplinary translational consortia to develop basic and clinical research in parallel could be pivotal to advance knowledge in the field. Although implementation of clinical trials for NDDs in paediatric populations is widely acknowledged as essential, safety concerns should guide each aspect of their design. Industry and academia should join forces to improve knowledge of the biology of brain development, identify the optimal timing of interventions, and translate these findings into new drugs, allowing for the needs of users and families, with support from regulatory agencies

Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem

Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as well