Visual perception alterations in COVID-19: a preliminary study

AIM: To compare the visual perception (color and chromatic-achromatic contrast vision) of a small cohort of COVID-19 patients at the time of infection and after 6mo with that of a healthy population matched for sex and age. METHODS: A total of 25 patients (9 females, 16 males, mean age: 54±10y) with COVID-19 hospitalized in the COVID-19 Unit of the University Clinical Hospital of Valladolid were recruited for this preliminary study. Visual perception, as determined by monocular measurement of contrast sensitivity function (CSF) and color vision was assessed in each patient using the Optopad test. The results obtained were then compared with those of a sample of 16 age- and sex-matched healthy controls (5 females, 11 males, mean age: 50±6y) in which the same measurement procedure was repeated. Statistically significant differences between groups were assessed using the Mann-Whitney U test. Measurements were repeated after a minimum follow-up period of 6mo and statistically significant differences between the two time points in each group were assessed using the Wilcoxon signed rank test. RESULTS: Discrimination thresholds (color and chromatic-achromatic contrast vision) and their corresponding sensitivity, calculated as the inverse of the discrimination threshold, were evaluated. Analysis of the data revealed higher contrast threshold results (i.e., worse contrast sensitivity) in the COVID-19 group than in the control group for all spatial frequencies studied in the Optopad-CSF achromatic test and most of the spatial frequencies studied in the Optopad-CSF chromatic test for the red-green and blue-yellow mechanisms. In addition, color threshold results in the COVID-19 group were also significantly higher (i.e., worse color sensitivity) for almost all color mechanisms studied in the Optopad-Color test. At 6mo, most of the differences found between the groups were maintained despite COVID-19 recovery. CONCLUSION: The present results provide preliminary evidence that visual perception may be impaired in COVID-19, even when the infection has passed. Although further research is needed to determine the precise causes of this finding, analysis of CSF and color vision could provide valuable information on the visual impact of COVID-19

Supercapacitance from cellulose and carbon nanotube nanocomposite fibers

Copyright © 2013 American Chemical SocietyACS AuthorChoice open access articleMultiwalled carbon nanotube (MWNT)/cellulose composite nanofibers have been prepared by electrospinning a MWNT/cellulose acetate blend solution followed by deacetylation. These composite nanofibers were then used as precursors for carbon nanofibers (CNFs). The effect of nanotubes on the stabilization of the precursor and microstructure of the resultant CNFs were investigated using thermogravimetric analysis, transmission electron microscopy and Raman spectroscopy. It is demonstrated that the incorporated MWNTs reduce the activation energy of the oxidative stabilization of cellulose nanofibers from 230 to 180 kJ mol–1. They also increase the crystallite size, structural order, and electrical conductivity of the activated CNFs (ACNFs). The surface area of the ACNFs increased upon addition of nanotubes which protrude from the fiber leading to a rougher surface. The ACNFs were used as the electrodes of a supercapacitor. The electrochemical capacitance of the ACNF derived from pure cellulose nanofibers is demonstrated to be 105 F g–1 at a current density of 10 A g–1, which increases to 145 F g–1 upon the addition of 6% of MWNTs.The authors would like to thank the [Engineering and Physical Sciences Research Council] EPSRC (EP/F036914/1 and EP/I023879/1), Guangdong and Shenzhen Innovative Research Team Program (No. 2011D052,KYPT20121228160843692), National Natural Science Foundation of China (Grant No. 21201175), R&D Funds for basic Research Program of Shenzhen (Grant No. JCYJ20120615140007998), and the Universities of Exeter and Manchester for funding this research

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

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation