Benchmarking Clustering and Classification Tasks using K-Means, Fuzzy C-Means and Feedforward Neural Networks optimized by PSO

Clustering is a widely used unsupervised learning technique across data mining and machine learning applications and finds frequent use in diverse fields ranging from astronomy, medical imaging, search and optimization, geology, geophysics and sentiment analysis to name a few. It is therefore important to verify the effectiveness of the clustering algorithms in question and to make reasonably strong arguments for the acceptance of the end results generated by the validity indices that measure the compactness and separability of clusters. This work aims to explore the successes and limitations of popular clustering mechanisms such as K-Means and Fuzzy C-Means by comparing their performance over publicly available benchmarking datasets that capture a variety of datapoint distributions as well as the number of features, especially from a computational point of view by incorporating techniques that alleviate some of the issues that plague these algorithms. In particular, sensitivity to initialization conditions and stagnation to local minima are explored. Further, an implementation of a feed-forward neural network using a branch of guided random search techniques, viz. Particle Swarm Optimization as the weight optimization strategy is explored to look at the same problem from a classification point of view. The algorithms implemented in this work are studied and their results compared, from which insights about their suitability of application to particular datasets can be obtained

The effect of cognitive fatigue on prefrontal cortex correlates of neuromuscular fatigue in older women

BACKGROUND: As the population of adults aged 65 and above is rapidly growing, it is crucial to identify physical and cognitive limitations pertaining to daily living. Cognitive fatigue has shown to adversely impact neuromuscular function in younger adults, however its impact on neuromuscular fatigue, and associated brain function changes, in older adults is not well understood. The aim of the study was to examine the impact of cognitive fatigue on neuromuscular fatigue and associated prefrontal cortex (PFC) activation patterns in older women. METHODS: Eleven older (75.82 (7.4) years) females attended two sessions and performed intermittent handgrip exercises at 30 % maximum voluntary contraction (MVC) until voluntary exhaustion after a 60-min control (watching documentary) and 60-min cognitive fatigue (performing Stroop Color Word and 1-Back tests) condition. Dependent measures included endurance time, strength loss, PFC activity (measured using fNIRS), force fluctuations, muscle activity, cardiovascular responses, and perceived discomfort. RESULTS: Participants perceived greater cognitive fatigue after the 60-min cognitive fatigue condition when compared to the control condition. While neuromuscular fatigue outcomes (i.e., endurance time, strength loss, perceived discomfort), force fluctuations, and muscle activity were similar across both the control and cognitive fatigue conditions, greater decrements in PFC activity during neuromuscular fatigue development after the cognitive fatigue condition were observed when compared to the control condition. CONCLUSION: Despite similar neuromuscular outcomes, cognitive fatigue was associated with blunted PFC activation during the handgrip fatiguing exercise that may be indicative of neural adaptation with aging in an effort to maintain motor performance. Examining the relationship between cognitive fatigue and neuromuscular output by imaging other motor-related brain regions are needed to provide a better understanding of age-related compensatory adaptations to perform daily tasks that involve some levels of cognitive demand and physical exercise, especially when older adults experience them sequentially

Use of Stand-Biased Desks to Reduce Sedentary Time in High School Students: A Pilot Study

Background: The purpose of this pilot study was to identify differences between sitting and standing time in high school students’ pre and post stand-biased desk intervention. Methods: ActivPal3™ activity monitors were affixed to 25 Bryan Collegiate High School students’ to monitor their standing time and activity levels. Data were collected at the beginning of the school year (fall) in traditional seated desks and in the spring in stand-biased desks. After attrition, 18 of the original 25 students were included in the final analysis. The physical activity data (steps) as well as standing and sitting time data provided by the monitors was used for within subject intervention analyses. Results: Descriptive statistics and a two-sided t-test were used to analyse differences between pre and post intervention sitting and standing times. Analysis indicated a significant reduction of sitting time post stand-biased desk intervention (p<0.0001) and a significant increase in standing time, post stand-biased desk intervention (p<0.0001). Analysis also revealed a non-statistically significant (p < 0.0619) average increase of 2,286 steps per school day when comparing mean steps pre-intervention (6,612) and post-intervention (8,898). Conclusions: Standing desks have the potential to reduce sedentary behavior and increase light to moderate physical activity for high school students during the school day

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

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

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

An evolutionary perspective on the co-occurrence of social anxiety disorder and alcohol use disorder

Social Anxiety Disorder (SAD) commonly co-occurs with, and often precedes, Alcohol Use Disorder (AUD). In this paper, we address the relationship between SAD and AUD by considering how natural selection left socially anxious individuals vulnerable to alcohol use, and by addressing the underlying mechanisms. We review research suggesting that social anxiety has evolved for the regulation of behaviors involved in reducing the likelihood or consequences of threats to social status. The management of potential threats to social standing is important considering that these threats can result in reduced cooperation or ostracism – and therefore to reduced access to coalitional partners, resources or mates. Alcohol exerts effects upon evolutionarily conserved emotion circuits, and can down-regulate or block anxiety (or may be expected to do so). As such, the ingestion of alcohol can artificially signal the absence or successful management of social threats. In turn, alcohol use may be reinforced in socially anxious people because of this reduction in subjective malaise, and because it facilitates social behaviors – particularly in individuals for whom the persistent avoidance of social situations poses its own threat (i.e., difficulty finding mates). Although the frequent co-occurrence of SAD and AUD is associated with poorer treatment outcomes than either condition alone, a richer understanding of the biological and psychosocial drives underlying susceptibility to alcohol use among socially anxious individuals may improve the efficacy of therapeutic interventions aimed at preventing or treating this comorbidity

Integrated genomic characterization of oesophageal carcinoma

Oesophageal cancers are prominent worldwide; however, there are few targeted therapies and survival rates for these cancers remain dismal. Here we performed a comprehensive molecular analysis of 164 carcinomas of the oesophagus derived from Western and Eastern populations. Beyond known histopathological and epidemiologic distinctions, molecular features differentiated oesophageal squamous cell carcinomas from oesophageal adenocarcinomas. Oesophageal squamous cell carcinomas resembled squamous carcinomas of other organs more than they did oesophageal adenocarcinomas. Our analyses identified three molecular subclasses of oesophageal squamous cell carcinomas, but none showed evidence for an aetiological role of human papillomavirus. Squamous cell carcinomas showed frequent genomic amplifications of CCND1 and SOX2 and/or TP63, whereas ERBB2, VEGFA and GATA4 and GATA6 were more commonly amplified in adenocarcinomas. Oesophageal adenocarcinomas strongly resembled the chromosomally unstable variant of gastric adenocarcinoma, suggesting that these cancers could be considered a single disease entity. However, some molecular features, including DNA hypermethylation, occurred disproportionally in oesophageal adenocarcinomas. These data provide a framework to facilitate more rational categorization of these tumours and a foundation for new therapies