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Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 individuals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each individual’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences.TeaserWe present a global effort to devise harmonization procedures necessary to meaningfully leverage big data.

Objective We sought to identify novel genes and to establish the contribution of known genes in a large cohort of patients with nonsyndromic sporadic polymicrogyria and epilepsy. Methods We enrolled participants with polymicrogyria and their parents through the Epilepsy Phenome/Genome Project. We performed phenotyping and whole exome sequencing (WES), trio analysis, and gene-level collapsing analysis to identify de novo or inherited variants, including germline or mosaic (postzygotic) single nucleotide variants, small insertion-deletion (indel) variants, and copy number variants present in leukocyte-derived DNA. Results Across the cohort of 86 individuals with polymicrogyria and epilepsy, we identified seven with pathogenic or likely pathogenic variants in PIK3R2, including four germline and three mosaic variants. PIK3R2 was the only gene harboring more than expected de novo variants across the entire cohort, and likewise the only gene that passed the genome-wide threshold of significance in the gene-level rare variant collapsing analysis. Consistent with previous reports, the PIK3R2 phenotype consisted of bilateral polymicrogyria concentrated in the perisylvian region with macrocephaly. Beyond PIK3R2, we also identified one case each with likely causal de novo variants in CCND2 and DYNC1H1 and biallelic variants in WDR62, all genes previously associated with polymicrogyria. Candidate genetic explanations in this cohort included single nucleotide de novo variants in other epilepsy-associated and neurodevelopmental disease-associated genes (SCN2A in two individuals, GRIA3, CACNA1C) and a 597-kb deletion at 15q25, a neurodevelopmental disease susceptibility locus. Significance This study confirms germline and postzygotically acquired de novo variants in PIK3R2 as an important cause of bilateral perisylvian polymicrogyria, notably with macrocephaly. In total, trio-based WES identified a genetic diagnosis in 12% and a candidate diagnosis in 6% of our polymicrogyria cohort. Our results suggest possible roles for SCN2A, GRIA3, CACNA1C, and 15q25 deletion in polymicrogyria, each already associated with epilepsy or other neurodevelopmental conditions without brain malformations. The role of these genes in polymicrogyria will be further understood as more patients with polymicrogyria undergo genetic evaluation.

To utilize data from the Australian Register of Antiepileptic Drugs in Pregnancy (APR) to determine the hazard of fetal malformation in the subsequent pregnancy or pregnancies in women with epilepsy following a pregnancy associated with a fetal malformation, and to identify factors relevant to the hazard.There was a 7.4% initial pregnancy fetal malformation rate. The subsequent pregnancy malformation rate was 4.2% if there was no initial pregnancy malformation, but 21.2% if there was an initial pregnancy malformation (O.R. = 6.1448, 95% C.I. 2.3396, 16.1386). For pregnancies where antiseizure medication (ASM) therapy was unchanged between pregnancies (N = 196), the initial pregnancy malformation rate was 10.2%, but 30.0% in the subsequent pregnancy if there was a malformation in the initial pregnancy, and 2.35% if there was none (O.R. = 17.7857, 95% C.I. 4.4847, 70.5361). A cohort comprising 24% of the women with fetal malformations in their initial pregnancies seemed to be intrinsically vulnerable to fetal malformation during successive pregnancies: when their seizure disorder type had been recorded all had genetic generalized epilepsies, compared with a 45.8% generalized epilepsy rate in women with initial but not subsequent pregnancy malformations (P = 0.0121).If fetal malformation had occurred in an initial ASM-treated pregnancy there was a significantly increased hazard of fetal malformation in the subsequent pregnancy, particularly if the woman involved had a genetic generalized epilepsy.

OBJECTIVE: Levetiracetam (LEV) is an effective antiseizure medicine, but 10%-20% of people treated with LEV report psychiatric side-effects, and up to 1% may have psychotic episodes. Pharmacogenomic predictors of these adverse drug reactions (ADRs) have yet to be identified. We sought to determine the contribution of both common and rare genetic variation to psychiatric and behavioral ADRs associated with LEV. METHODS: This case-control study compared cases of LEV-associated behavioral disorder (n = 149) or psychotic reaction (n = 37) to LEV-exposed people with no history of psychiatric ADRs (n = 920). All samples were of European ancestry. We performed genome-wide association study (GWAS) analysis comparing those with LEV ADRs to controls. We estimated the polygenic risk scores (PRS) for schizophrenia and compared cases with LEV-associated psychotic reaction to controls. Rare variant burden analysis was performed using exome sequence data of cases with psychotic reactions (n = 18) and controls (n = 122). RESULTS: Univariate GWAS found no significant associations with either LEV-associated behavioural disorder or LEV-psychotic reaction. PRS analysis showed that cases of LEV-associated psychotic reaction had an increased PRS for schizophrenia relative to contr ols (p = .0097, estimate = .4886). The rare-variant analysis found no evidence of an increased burden of rare genetic variants in people who had experienced LEV-associated psychotic reaction relative to controls. SIGNIFICANCE: The polygenic burden for schizophrenia is a risk factor for LEV-associated psychotic reaction. To assess the clinical utility of PRS as a predictor, it should be tested in an independent and ideally prospective cohort. Larger sample sizes are required for the identification of significant univariate common genetic signals or rare genetic signals associated with psychiatric LEV ADRs.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted ‘gold-standard’ subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.

IntroductionOne outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualise on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide.MethodsThe Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonised a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance.ResultsOur pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. Overall, after including a border-zone around lesions, the developed MELD FCD surface-based algorithm had a sensitivity of 67% and a specificity of 54% on the withheld test cohort, and a sensitivity of 85% on a restricted subcohort of seizure free patients with FCD type IIB who had T1 and FLAIR MRI data.ConclusionsThis multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions.HighlightsThis large, multi-centre, multi-scanner neuroimaging cohort captures the heterogeneity of histopathological subtypes and imaging features of patients with FCD.We developed a robust and interpretable surface-based algorithm which detects FCDs with a sensitivity of 67% and a specificity of 54%.The algorithm generates individual patient reports that “open the AI black-box” highlighting predicted lesion locations, alongside the imaging features and their relative saliency to the classifier.

Epilepsy affects all age groups and is one of the most common and most disabling neurological disorders. The accurate diagnosis of seizures is essential as some patients will be misdiagnosed with epilepsy, whereas others will receive an incorrect diagnosis. Indeed, errors in diagnosis are common, and many patients fail to receive the correct treatment, which often has severe consequences. Although many patients have seizure control using a single medication, others require multiple medications, resective surgery, neuromodulation devices or dietary therapies. In addition, one-third of patients will continue to have uncontrolled seizures. Epilepsy can substantially impair quality of life owing to seizures, comorbid mood and psychiatric disorders, cognitive deficits and adverse effects of medications. In addition, seizures can be fatal owing to direct effects on autonomic and arousal functions or owing to indirect effects such as drowning and other accidents. Deciphering the pathophysiology of epilepsy has advanced the understanding of the cellular and molecular events initiated by pathogenetic insults that transform normal circuits into epileptic circuits (epileptogenesis) and the mechanisms that generate seizures (ictogenesis). The discovery of500 genes associated with epilepsy has led to new animal models, more precise diagnoses and, in some cases, targeted therapies.

Objective To evaluate long-term (up to 5.5 years) safety, seizure reduction, and maintenance of efficacy of the antiepileptic drug (AED) lacosamide as adjunctive treatment in an open-label extension trial (SP774; ClinicalTrials.gov: NCT00515619). Methods Three hundred and seventy-six adults with partial-onset seizures taking 1–3 AEDs enrolled following completion of a double-blind trial of adjunctive lacosamide. During open-label treatment, dosage of lacosamide (100–800 mg/day) and/or concomitant AEDs could be adjusted to optimize tolerability and seizure control. Results Kaplan–Meier estimates of patient retention were 74.5% at 12 months, 52.9% at 36 months, and 40.6% at 60 months; median open-label treatment duration was 1183 days (~3.2 years). The most frequently reported treatment-emergent adverse events were dizziness (24.2%), headache (14.4%), diplopia (13.8%), and nasopharyngitis (13.8%); 9.0% of patients discontinued due to adverse events, most commonly dizziness (1.3%). Median percent reduction in 28-day seizure frequency from baseline of the double-blind trial was 49.9% overall, 55.4% for 1-year completers, and 62.3% for 3-year completers. Overall, 50.0% of patients were considered ≥50% responders (achieved ≥50% reduction in 28-day seizure frequency); 55.9% of 1-year completers and 63.0% of 3-year completers were ≥50% responders. Conclusion In eligible patients who entered the open-label extension trial, lacosamide was generally well tolerated. For most patients within each yearly completer cohort, seizure reduction was maintained over time.

Review(s) of: Guerrilla Diplomacy: Rethinking International Relations, by Daryl Copeland. Boulder, CO: Lynne Rienner; 2009, xiv + 311 pp.

(18)F-FDG PET is an accurate and reliable technique for localizing medically refractory temporal lobe epilepsy, but widespread use has been hindered by limited reimbursement in many countries because of the high cost of traditional PET equipment and radioisotopes. Additionally, the place of FDG PET as a cost-effective tool for presurgical evaluation of epilepsy has been questioned because of limited data showing that FDG PET provides localization information incremental to that provided by more established techniques, particularly MRI and ictal electroencephalography (EEG). Three-dimensional (3D), large-field-of-view, sodium iodide crystal-based scanners have lower equipment and running costs and better multiplanar resolution than traditional 2-dimensional bismuth germinate (BGO) systems but have not yet been validated for evaluation of epilepsy. Our purpose was to investigate the localization rate, accuracy, and prognostic value of FDG PET images acquired on a 3D, large-field-of-view, sodium iodide crystal-based PET scanner in the presurgical evaluation of intractable partial epilepsy. We also wanted to establish the incremental value of FDG PET over established MRI and ictal EEG techniques.Fifty-five patients who were surgical candidates because of medically refractory partial epilepsy were examined. For most of these patients, the lesions had not been clearly localized on conventional assessment. The FDG PET scans were reviewed independently by 2 reviewers who were unaware of the patients' clinical details, ictal EEG findings, and volumetric MRI results, and the FDG PET results were correlated with those of MRI and EEG and with postsurgical outcome.Forty-two patients (76%) had localizing FDG PET images (37 temporal, 5 extratemporal). The ictal EEG recordings were localizing in 66%, and the MRI findings were localizing in 27% (which increased to 35% after the MRI findings were reviewed again after PET). Concordance between the site of the PET localizations and the site of the MRI or EEG localizations was 100%. The PET images were localizing in 63% and 69% of patients with nonlocalizing ictal EEG and MRI findings, respectively. Twenty-one of 24 patients who subsequently underwent epilepsy surgery had localizing FDG PET images; of these 21 patients, 18 (86%) had a class I outcome. Multiple regression analysis showed the FDG PET results to be predictive of postsurgical outcome independently of the MRI findings.For intractable partial epilepsy, FDG PET using a 3D, large-field-of-view, sodium iodide crystal-based scanner provided clinically useful localizing information that was at least as accurate as the results reported for traditional BGO-based scanners. The PET images provided prognostically significant localization information incremental to that provided by volumetric MRI and ictal EEG, particularly if 1 of these studies was nonlocalizing.

This study reports quantitative measurements of the accuracy of two popular voxel-based registration algorithms--Woods' automated image registration algorithm and mutual information correlation--and compares these with conventional surface matching (SM) registration.The registration algorithms were compared (15 different matches each) for (a) three-dimensional brain phantom images, (b) an ictal SPECT image from a patient with partial epilepsy matched to itself after modification to simulate changes in the cerebral blood flow pattern and (c) ictal/interictal SPECT images from 15 patients with partial epilepsy. Blinded visual ranking and localization of the subtraction images derived from the patient images were also performed.Both voxel-based registration methods were more accurate than SM registration (P0.0005). Automated image registration algorithm was more accurate than mutual information correlation for the computer-simulated ictal/interictal images and the patient ictal/interictal studies (P0.05). The subtraction SPECTs from SM were poorer in visual ranking more often than the voxel-based methods (P0.05).Voxel intensity-based registration algorithms provide significant improvement in ictal/interictal SPECT registration accuracy and result in a clinically detectable improvement in the subtraction SPECT images.

The last thirty years of the 20th century have witnessed remarkable economic success in countries of East Asia which, while the growth and prosperity is not uniformly distributed, is unequalled in modern history in both the speed and extent of its impact. The result is that on the doorstep of a new century, the Asia-Pacific region as a whole constitutes a vital engine force for the global economy, and, at the same time, is itself deeply affected by the impacts of globalisation — in particular the factors of trade, information and technology — that are transforming the global economy everywhere. Trade, in particular, has been growing faster than output and is projected to continue to grow at a rapid rate. Driven in part by technological change, economic integration has been deepening in ways that signal fundamental change in the global community.1 In Asia, the emergence of trans-border growth triangles that interlock regional economies is one manifestation of this trend.

Nuclear-weapon-free zones (NWFZ) are regionally derived initiatives. In this regard they are qualitatively different from other parts of the international nuclear weapons and arms control agenda where the initiative derives substantially from the acknowledged nuclear-weapons states (NWS). For all practical purposes this means that the lion’s share of the nuclear security discourse and agenda is promoted, indeed defined, by those acknowledged NWS. The stage reached on the international agenda — with the indefinite renewal of the Nuclear Non-Proliferation Treaty (NPT) in 1995, and the adoption of the Comprehensive Test Ban Treaty (CTBT) and the International Court of Justice (ICJ) Advisory Opinion on the legality of nuclear weapons in 1996 — has refocused attention on NWFZ and their utility in advancing matters further down the twin tracks of genuine non-proliferation and real nuclear disarmament.

To determine the benefit of the addition of ipratropium bromide to beta-agonist therapy of acute exacerbations of chronic obstructive pulmonary disease.The trial was randomized and double blinded.The study was conducted in the emergency department of Parkland Memorial Hospital, a busy, inner-city, county hospital.Patients were treated in the medicine emergency department with either the standard regimen of nebulized isoetharine, 0.5 mL of a 1% solution (5.0 mg) diluted to 2.0 mL with normal saline every hour (control group) or with the same regimen plus ipratropium bromide, 54 micrograms (three puffs) after the first isoetharine treatment and 36 micrograms (two puffs) after the second and fourth (experimental group). A placebo metered-dose inhaler used in the same manner as the ipratropium blinded the study to both the patients and medical personnel.The group treated with the addition of ipratropium (30) was discharged from the ED an average of 91 minutes (P less than .05) sooner than the control group (25) and required on the average one less isoetharine treatment (P less than .05). The pulmonary functions tested, forced expiratory volume in the first second, and the forced vital capacity were the same in the two groups initially and on discharge, as identical discharge criteria were used in each group.The addition of ipratropium to standard beta-agonist treatment of chronic obstructive pulmonary disease exacerbations shortens the duration of treatment required in the ED.

The poet John Montague explored the effects on a community when a subordinate linguistic culture collapsed under pressures from a more dominant culture.1 This discussion concentrates on language because it has been held to constitute the essence of a culture. George Steiner put the point this way: Language is both the container and the shaping spirit of the ways in which we experience the world. Every single language embodies and gives expression to a particular way of organising perceiving, understanding reality. Human senses are, broadly speaking, the same throughout the earth. But the mental picture of the world which makes up that complex living framework of social existence which we call a culture varies immensely from community to community. And it is of this variety that language is the pre-eminent medium and preserver.2

In 2005, a major collaboration in Melbourne Australia successfully completed implementing a major medical informatics infrastructure - this is now being used for discovery research and has won significant expansion funding for 2006 - 2009. The convergence of life sciences, healthcare, and information technology is now driving research into the fundamentals of disease causation. Key to enabling this is collating data in sufficient numbers of patients to ensure studies are adequately powered. The Molecular Medicine Informatics Model (MMIM) is a 'virtual' research repository of clinical, laboratory and genetic data sets. Integrated data, physically located within independent hospital and research organisations can be searched and queried seamlessly via a federated data integrator. Researchers must gain authorisation to access data, and inform/obtain permission from the data owners, before the data can be accessed. The legal and ethical issues surrounding the use of this health data have been addressed so data complies with privacy requirements. The MMIM platform has also solved the issue of record linking individual cases and integrating data sources across multiple institutions and multiple clinical specialties. Significant research outcomes already enabled by the MMIM research platform include epilepsy seizure analyses for responders / non responders to therapy; sensitivity of faecal occult blood testing for asymptomatic colorectal cancer and advanced adenomas over a 25-year experience in colorectal cancer screening; subsite-specific colorectal cancer in diabetic and non diabetic patients; and the influence of language spoken on colorectal cancer diagnosis, management and outcomes. Ultimately the infrastructure of MMIM enables discovery research to be accessible via the Web with security, intellectual property and privacy addressed.