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Background: Polymicrogyria refers to the disruption of normal cerebral cortical development late in neuronal migration or in early cortical organization. Although patients with polymicrogyria feature relatively favorable motor outcomes, polymicrogyric lesions accompanied by extensive unilateral hemispheric atrophy and ipsilateral brainstem atrophy may induce poorer motor outcomes. This study is the first to employ transcranial magnetic stimulation (TMS) and diffusion tensor imaging (DTI) to characterize changes to motor organization and white matter tracts induced by polymicrogyria.Case Presentation: We document a case of a 16-year-old female with left hemiplegic unilateral polymicrogyria associated with ipsilateral brainstem atrophy. Magnetic resonance imaging (MRI) of the brain revealed unilateral polymicrogyria to have affected anterior cortical areas, including the perisylvian region on the right side. The right halves of the brain and brainstem were significantly smaller than the left halves. Although our patient was found to exhibit cortical dysplasia of the right frontoparietal and sylvian fissure areas and a decreased number of fibers in the corticospinal tract (CST) of the affected side on DTI, the connectivity of the CST was preserved up to the motor cortex. We also measured the cross-sectional area of the CST at the level of the pons. In TMS, contralateral motor evoked potentials (MEPs) were evoked from both hands, but the ipsilateral MEPs were evoked only from the left hand. The left hand featured a long duration, polyphasic pattern of contralateral MEPs.Discussion and Conclusion: TMS revealed that the concurrent bilateral projections to the paretic hand from the affected and unaffected hemispheres and contralateral MEPs in the paretic hand were polyphasic, indicating delayed electrophysiological maturation or a pathologic condition of the corticospinal motor pathways. In DTI, the cross-sectional area of the CST at the level of the pons on the affected side was smaller than that on the unaffected side. These DTI findings reveal an inadequate CST volume. Despite extensive brain malformation and ipsilateral brainstem atrophy, our patient had less severe motor dysfunction and presented with involuntary mirror movements. Mirror movements in the paretic hand are considered to indicate ipsilateral corticospinal projections from the unaffected hemisphere and may suggest favorable motor outcomes in early brain injury. [ABSTRACT FROM AUTHOR]

Background: Triple-Negative Breast Cancer (TNBC) is an aggressive and complex subtype of breast cancer. The current biomarkers used in the context of breast cancer treatment are highly dependent on the targeting of oestrogen receptor, progesterone receptor, or HER2, resulting in treatment failure and disease recurrence and creating clinical challenges. Thus, there is still a crucial need for the improvement of TNBC treatment; the discovery of effective biomarkers that can be easily translated to the clinics is essential.Methods: We report an approach for the discovery of biomarkers that can predict tumour relapse and pathologic complete response (pCR) in TNBC on the basis of mRNA expression quantified using the NanoString nCounter Immunology Panel. To overcome the limited sample size, prediction models based on random Forest were constructed using the differentially expressed genes (DEGs) as selected features. We also evaluated the differences between pre- and post-treatment groups aiming for the combinatorial assessment of pCR and relapse using additive models in edgeR.Results: We identify nine and 13 DEGs strongly associated with pCR and relapse, respectively, from 579 immune genes in a small number of samples (n = 55) using edgeR. An additive model for the comparison of pre- and post-treatment groups via the adjustment of the independent subject in the relapse group revealed associations for 41 genes. Comprehensive analysis indicated that our prediction models outperformed those constructed using features extracted from the existing feature selection model Elastic Net in terms of accuracy. The prediction models were assessed using a randomization test to validate the robustness (empirical P for the model of pCR = 0.015 and empirical P for the model of relapse = 0.018). Furthermore, three DEGs (FCER1A, EDNRB, and TGFBI) in the model of relapse showed prognostic significance for predicting the survival of patients with cancer through Cox proportional hazards regression model-based survival analysis.Conclusion: Gene expression quantified via the NanoString nCounter Immunology Panel can be seamlessly analysed using edgeR, even considering small sample sizes. Our approach provides a scalable framework that can easily be applied for the discovery of biomarkers based on the NanoString nCounter Immunology Panel.Data Availability: The source code will be available from github at https://github.com/sungheep/nanostring . [ABSTRACT FROM AUTHOR]