MULTIPLE INPUT SINGLE OUTPUT CONVERTER WITH UNEVEN LOAD SHARING CONTROL FOR IMPROVED SYSTEM EFFICIENCY

This paper presents the development and study of multiple-input single-output converter (MISO) for the DC House project that utilizes a controller to maximize the overall converter’s efficiency. The premise of this thesis is to create uneven load current sharing between the converters at different loading conditions in order to maximize the efficiency of the overall MISO converter. The goal is to find a proper ratio of current from each converter to the total load current of the MISO system to achieve the greatest efficiency. The Arduino microcontroller is implemented to achieve this goal. The design and operation of the MISO converter with the proposed controller will be explained in this paper. The design and operation of the converter was tested and verified through simulation in LTSpice in addition to hardware implementation. Different ratios of current from each converter were used to fully test the MISO converter. For the 5A and 6A load current, the maximum efficiencies were reached with the 70% / 30% ratio case, with efficiencies of 94.91% and 95.07%, respectively. For 7A load current, the maximum efficiency was reached with the 60% / 40% ratio case, with an efficiency of 94.59%. The results were then compared with those obtained from the equal current sharing cases. For the cases tested, the efficiency of the unequal current sharing outperforms that obtained from the equal current sharing method

Going beyond (electronic) patient-reported outcomes: harnessing the benefits of smart technology and ecological momentary assessment in cancer survivorship research

Rapid developments in digital mobile and sensor technology have facilitated the active and passive collection of detailed, personalized data in increasingly affordable ways. Researchers may be familiar with the daily diary, portable computers, or the pedometer for the collection of patientreported outcomes (PRO) in cancer survivorship research. Such methods, termed ecological momentary assessment (EMA), have evolved with technological advances, e.g., collecting data or providing interventions (ecological momentary intervention, EMI) via apps or devices such as smartphones. These smart technology-adapted sEMA/ sEMI methods are more widely used in affective disorders or addictive behavior research but are currently still under-utilized in cancer survivorship research. A recent scoping review on the use of active EMA among cancer survivors identified twelve articles published between 1993 and 2018. Most of the included studies in that review used portable computers. This commentary will discuss the utility of sEMA/sEMI in cancer survivorship research and call for action to advance this area of science

Recurrent Modification of a Conserved Cis-Regulatory Element Underlies Fruit Fly Pigmentation Diversity

The development of morphological traits occurs through the collective action of networks of genes connected at the level of gene expression. As any node in a network may be a target of evolutionary change, the recurrent targeting of the same node would indicate that the path of evolution is biased for the relevant trait and network. Although examples of parallel evolution have implicated recurrent modification of the same gene and cis-regulatory element (CRE), little is known about the mutational and molecular paths of parallel CRE evolution. In Drosophila melanogaster fruit flies, the Bric-à-brac (Bab) transcription factors control the development of a suite of sexually dimorphic traits on the posterior abdomen. Female-specific Bab expression is regulated by the dimorphic element, a CRE that possesses direct inputs from body plan (ABD-B) and sex-determination (DSX) transcription factors. Here, we find that the recurrent evolutionary modification of this CRE underlies both intraspecific and interspecific variation in female pigmentation in the melanogaster species group. By reconstructing the sequence and regulatory activity of the ancestral Drosophila melanogaster dimorphic element, we demonstrate that a handful of mutations were sufficient to create independent CRE alleles with differing activities. Moreover, intraspecific and interspecific dimorphic element evolution proceeded with little to no alterations to the known body plan and sex-determination regulatory linkages. Collectively, our findings represent an example where the paths of evolution appear biased to a specific CRE, and drastic changes in function were accompanied by deep conservation of key regulatory linkages. © 2013 Rogers et al

High-quality gene assembly directly from unpurified mixtures of microarray-synthesized oligonucleotides

To meet the growing demand for synthetic genes more robust, scalable and inexpensive gene assembly technologies must be developed. Here, we present a protocol for high-quality gene assembly directly from low-cost marginal-quality microarray-synthesized oligonucleotides. Significantly, we eliminated the time- and money-consuming oligonucleotide purification steps through the use of hybridization-based selection embedded in the assembly process. The protocol was tested on mixtures of up to 2000 oligonucleotides eluted directly from microarrays obtained from three different chip manufacturers. These mixtures containing <5% perfect oligos, and were used directly for assembly of 27 test genes of different sizes. Gene quality was assessed by sequencing, and their activity was tested in coupled in vitro transcription/translation reactions. Genes assembled from the microarray-eluted material using the new protocol matched the quality of the genes assembled from >95% pure column-synthesized oligonucleotides by the standard protocol. Both averaged only 2.7 errors/kb, and genes assembled from microarray-eluted material without clonal selection produced only 30% less protein than sequence-confirmed clones. This report represents the first demonstration of cost-efficient gene assembly from microarray-synthesized oligonucleotides. The overall cost of assembly by this method approaches 5¢ per base, making gene synthesis more affordable than traditional cloning

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

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

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

Spermatogenesis-Specific Features of the Meiotic Program in Caenorhabditis elegans

In most sexually reproducing organisms, the fundamental process of meiosis is implemented concurrently with two differentiation programs that occur at different rates and generate distinct cell types, sperm and oocytes. However, little is known about how the meiotic program is influenced by such contrasting developmental programs. Here we present a detailed timeline of late meiotic prophase during spermatogenesis in Caenorhabditis elegans using cytological and molecular landmarks to interrelate changes in chromosome dynamics with germ cell cellularization, spindle formation, and cell cycle transitions. This analysis expands our understanding C. elegans spermatogenesis, as it identifies multiple spermatogenesis-specific features of the meiotic program and provides a framework for comparative studies. Post-pachytene chromatin of spermatocytes is distinct from that of oocytes in both composition and morphology. Strikingly, C. elegans spermatogenesis includes a previously undescribed karyosome stage, a common but poorly understood feature of meiosis in many organisms. We find that karyosome formation, in which chromosomes form a constricted mass within an intact nuclear envelope, follows desynapsis, involves a global down-regulation of transcription, and may support the sequential activation of multiple kinases that prepare spermatocytes for meiotic divisions. In spermatocytes, the presence of centrioles alters both the relative timing of meiotic spindle assembly and its ultimate structure. These microtubule differences are accompanied by differences in kinetochores, which connect microtubules to chromosomes. The sperm-specific features of meiosis revealed here illuminate how the underlying molecular machinery required for meiosis is differentially regulated in each sex

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas