A Semantic Model to Study Neural Organization of Language in Bilingualism

A neural network model of object semantic representation is used to simulate learning of new words from a foreign language. The network consists of feature areas, devoted to description of object properties, and a lexical area, devoted to words representation. Neurons in the feature areas are implemented as Wilson-Cowan oscillators, to allow segmentation of different simultaneous objects via gamma-band synchronization. Excitatory synapses among neurons in the feature and lexical areas are learned, during a training phase, via a Hebbian rule. In this work, we first assume that some words in the first language (L1) and the corresponding object representations are initially learned during a preliminary training phase. Subsequently, second-language (L2) words are learned by simultaneously presenting the new word together with the L1 one. A competitive mechanism between the two words is also implemented by the use of inhibitory interneurons. Simulations show that, after a weak training, the L2 word allows retrieval of the object properties but requires engagement of the first language. Conversely, after a prolonged training, the L2 word becomes able to retrieve object per se. In this case, a conflict between words can occur, requiring a higher-level decision mechanism

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

An Emergent Model of Multisensory Integration in Superior Colliculus Neurons

Neurons in the cat superior colliculus (SC) integrate information from different senses to enhance their responses to cross-modal stimuli. These multisensory SC neurons receive multiple converging unisensory inputs from many sources; those received from association cortex are critical for the manifestation of multisensory integration. The mechanisms underlying this characteristic property of SC neurons are not completely understood, but can be clarified with the use of mathematical models and computer simulations. Thus the objective of the current effort was to present a plausible model that can explain the main physiological features of multisensory integration based on the current neurological literature regarding the influences received by SC from cortical and subcortical sources. The model assumes the presence of competitive mechanisms between inputs, nonlinearities in NMDA receptor responses, and provides a priori synaptic weights to mimic the normal responses of SC neurons. As a result, it provides a basis for understanding the dependence of multisensory enhancement on an intact association cortex, and simulates the changes in the SC response that occur during NMDA receptor blockade. Finally, it makes testable predictions about why significant response differences are obtained in multisensory SC neurons when they are confronted with pairs of cross-modal and within-modal stimuli. By postulating plausible biological mechanisms to complement those that are already known, the model provides a basis for understanding how SC neurons are capable of engaging in this remarkable process

Prognostic value and kinetics of circulating endothelial cells in patients with recurrent glioblastoma randomised to bevacizumab plus lomustine, bevacizumab single agent or lomustine single agent. A report from the Dutch Neuro-Oncology Group BELOB trial

Background:Angiogenesis is crucial for glioblastoma growth, and anti-vascular endothelial growth factor agents are widely used in recurrent glioblastoma patients. The number of circulating endothelial cells (CECs) is a surrogate marker for endothelial damage. We assessed their kinetics and explored their prognostic value in patients with recurrent glioblastoma.Methods:In this side study of the BELOB trial, 141 patients with recurrent glioblastoma were randomised to receive single-agent bevacizumab or lomustine, or bevacizumab plus lomustine. Before treatment, after 4 weeks and after 6 weeks of treatment, CECs were enumerated.Results:The number of CECs increased during treatment with bevacizumab plus lomustine, but not during treatment in the single-agent arms. In patients treated with lomustine single agent, higher absolute CEC numbers after 4 weeks (log 10 CEC hazard ratio (HR) 0.41, 95% CI 0.18-0.91) and 6 weeks (log 10 CEC HR 0.16, 95% CI 0.05-0.56) of treatment were associated with improved overall survival (OS). Absolute CEC numbers in patients receiving bevacizumab plus lomustine or bevacizumab single agent were not associated wit

Is fluorescein-guided technique able to help in resection of high-grade gliomas?

OBJECT: Fluorescein, a dye that is widely used as a fluorescent tracer, accumulates in cerebral areas where the blood-brain barrier is damaged. This quality makes it an ideal dye for the intraoperative visualization of high-grade gliomas (HGGs). The authors report their experience with a new fluorescein-guided technique for the resection of HGGs using a dedicated filter on the surgical microscope. METHODS: The authors initiated a prospective Phase II trial (FLUOGLIO) in September 2011 with the objective of evaluating the safety of fluorescein-guided surgery for HGGs and obtaining preliminary evidence regarding its efficacy for this purpose. To be eligible for participation in the study, a patient had to have suspected HGG amenable to complete resection of the contrast-enhancing area. The present report is based on the analysis of the short- and long-term results in 20 consecutive patients with HGGs (age range 45-74 years), enrolled in the study since September 2011. In all cases fluorescein (5-10 mg/kg) was injected intravenously after intubation. Tumor resection was performed with microsurgical technique and fluorescence visualization by means of BLUE 400 or YELLOW 560 filters on a Pentero microscope. RESULTS: The median preoperative tumor volume was 30.3 cm(3) (range 2.4-87.8 cm(3)). There were no adverse reactions related to fluorescein administration. Complete removal of contrast-enhanced tumor was achieved in 80% of the patients. The median duration of follow-up was 10 months. The 6-months progression-free survival rate was 71.4% and the median survival was 11 months. CONCLUSIONS: Analysis of these 20 cases suggested that fluorescein-guided technique with a dedicated filter on the surgical microscope is safe and allows a high rate of complete resection of contrast-enhanced tumor as determined on early postoperative MRI. Clinical trial registration no.: 2011-002527-18 (EudraCT)