ORCID Profile
0000-0001-8932-4578
Current Organisation
University of New England
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Publisher: Cold Spring Harbor Laboratory
Date: 20-12-2019
DOI: 10.1101/2019.12.19.883405
Abstract: The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre s le of adult epilepsy patients. Diffusion-weighted MRI data were analyzed from 1,069 non-epileptic controls and 1,249 patients: temporal lobe epilepsy with hippoc al sclerosis (N=599), temporal lobe epilepsy with normal MRI (N=275), genetic generalized epilepsy (N=182) and nonlesional extratemporal epilepsy (N=193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fiber tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at p .001). Across “all epilepsies” lower fractional anisotropy was observed in most fiber tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. Less robust effects were seen with mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippoc al sclerosis in the ipsilateral parahippoc al cingulum and external capsule, with smaller effects across most other tracts. Those with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippoc al sclerosis. Patients with generalized and extratemporal epilepsies had pronounced differences in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and in mean diffusivity of the anterior corona radiata . Earlier age of seizure onset and longer disease duration were associated with a greater extent of microstructural abnormalities in patients with hippoc al sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibers in a large multicentre study of epilepsy. Overall, epilepsy patients showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding new insights into pathological substrates that may be used to guide future therapeutic and genetic studies.
Publisher: Springer Science and Business Media LLC
Date: 21-04-2014
DOI: 10.1038/ONC.2014.106
Abstract: A feature of many gliomas is the lification of the epidermal growth factor receptor (EGFR), resulting in its overexpression. Missense mutations or deletions within the extracellular domain are associated with this lification and can lead to constitutive activation of the receptor, with the Domain I/II deletion, EGFRvIII, being the most common. These changes have also been associated with increased sensitivity to EGFR inhibition using small molecule inhibitors. We have expressed, in human glioma cells, EGFR containing four glioma-specific EGFR missense mutations within Domain IV (C620Y, C624F, C628Y and C636Y) to analyze their biological properties and sensitivity to EGFR inhibition. One of these mutants, C620Y, exhibited an enhanced basal phosphorylation, which was partially dependent on an EGFR-ligand autocrine loop. All Domain IV mutants responded equally as well as wildtype EGFR (wtEGFR) to ligand stimulation. Biochemical analysis revealed that a pre-formed, disulfide-bonded dimer associated with these mutations was underglycosylated, inactive and cytoplasmically retained. Ligand stimulation resulted in the formation of a tyrosine-phosphorylated, disulfide-bonded dimer for all Domain IV mutants but not for wtEGFR. Following treatment with the next-generation, irreversible pan-ErbB inhibitor dacomitinib, the C620Y, C624F and EGFRvIII mutants were inactivated, covalently dimerized and were retained in the cytoplasm, resulting in cell-surface receptor loss and, for C620Y and C624F, decreased binding of EGF. Dacomitinib treatment significantly reduced the in vivo growth of human glioma xenografts bearing C620Y, but not wtEGFR. Collectively, these data indicate that the unique biochemical traits of Domain IV EGFR cysteine mutants can be exploited for enhanced sensitivity to EGFR small molecule inhibitors, with potential clinical applications.
Publisher: Oxford University Press (OUP)
Date: 30-01-2018
DOI: 10.1093/BRAIN/AWX341
Publisher: MDPI AG
Date: 22-12-2021
DOI: 10.3390/HORTICULTURAE8010011
Abstract: In 2020, mango (Mangifera indica) exports contributed over 40 million tons, worth around US$20 billion, to the global economy. Only 10% of this contribution was made from African countries including Ghana, largely due to lower investment in the sector and general paucity of research into the mango value chain, especially production, quality and volume. Considering the global economic importance of mango coupled with the gap in the use of the remote sensing technology in the sector, this study tested the hypothesis that phenological stages of mango can be retrieved from Sentinel-2 (S2) derived time series vegetation indices (VIs) data. The study was conducted on four mango farms in the Yilo Krobo Municipal Area of Ghana. Seasonal (temporal) growth curves using four VIs (NDVI, GNDVI, EVI and SAVI) for the period from 2017 to 2020 were derived for each of the selected orchards and then aligned with five known phenology stages: Flowering/Fruitset (F/FS), Fruit Development (FRD), Maturity/Harvesting (M/H), Flushing (FLU) and Dormancy (D). The significance of the variation “within” and “between” farms obtained from the VI metrics of the S2 data were tested using single-factor and two-factor analysis of variance (ANOVA). Furthermore, to identify which specific variable pairs (phenology stages) were significantly different, a Tukey honest significant difference (HSD) post-hoc test was conducted, following the results of the ANOVA. Whilst it was possible to differentiate the phenological stages using all the four VIs, EVI was found to be the best related with p 0.05 for most of the studied farms. A distinct annual trend was identified with a peak in June/July and troughs in December/January. The derivation of remote sensing based ‘time series’ growth profiles for commercial mango orchards supports the ‘benchmarking’ of annual and seasonal orchard performance and therefore offers a near ‘real time’ technology for identifying significant variations resulting from pest and disease incursions and the potential impacts of seasonal weather variations.
Publisher: Elsevier BV
Date: 03-2013
DOI: 10.1016/J.YEBEH.2012.09.006
Abstract: It has been estimated that JME (juvenile myoclonic epilepsy), when compared to other adult epilepsy syndromes, is most likely to have a genetic cause. However, decades of research have not brought us closer to finding a single 'JME gene' that is important on a population basis. Is this due in part to the genetic complexity of the syndrome, the cryptic nature of the genes of effect, or perhaps because JME is not one condition at all but many? Before we can begin to harness the power of next-generation sequencing techniques, we must first reduce JME down to lacunae of homogeneity--using increasingly more sophisticated phenotyping tools. The current technological advances in gene sequencing have been used to dramatic effect to identify single gene causes in rare syndromes and identify risk variants in malignancies. Filtering the variety of the human exome or genome down into a handful of biologically plausible candidates now relies on a pipeline of biostatistics, software, and functional analyses. It is simply unacceptable to return uncertain findings to the clinical domain and, therefore, it is crucial that pathogenicity is fully determined before families receive genetic counseling and test results.
Publisher: Wiley
Date: 29-05-2020
DOI: 10.1002/HBM.25037
Abstract: Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller‐scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well‐established by the ENIGMA Consortium, ENIGMA‐Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing s le sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event‐based modeling analysis. We explore age of onset‐ and duration‐related features, as well as phenomena‐specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA‐Epilepsy.
No related grants have been discovered for Azeem Khan.