Utilizing neural networks to proactively monitor energy usage in City of Rochester buildings

Energy usage within buildings in the United States is a very important topic because of the current price of natural gas, steam, and electricity and the ever-increasing depletion of fossil fuels. Therefore, it is necessary to carefully analyze building energy consumption. Currently, there are several methods used for analyzing a solitary building\u27s energy usage. One method involves the use of a neural network (NN) model. The current use of NN for building energy prediction typically requires the collection of hourly energy usage data from a single building using data loggers during several different seasons and occupancy levels in order to create a robust training data set for supervised training of the NN model. Well designed NN energy models are able to predict with a high degree of accuracy (+/- 5 to 10 percent on average), but the upfront data collection can prove to be quite time consuming. Therefore for groups of buildings on a campus or in a city, an alternative method for predicting energy consumption using NNs must be explored. Using readily available monthly energy and weather data from several buildings owned by the city of Rochester, New York, three methods involving NN models are created and validated to find the optimal NN configuration for predicting energy usage. The results of these trials have shown that it is feasible to utilize NNs trained only on readily available data as a warning system for buildings in need of a thorough check and possibly preventative maintenance. Based on the results of the validation trials, it was discovered that the predictive ability of the multiple building trials is poor due to the variability of the data. The usage of data from similar buildings and single buildings improved the predictive ability. The best prediction results occurred by using a single output network trained on data from a solitary building

A shared role for sonic hedgehog signalling in patterning chondrichthyan gill arch appendages and tetrapod limbs.

Chondrichthyans (sharks, skates, rays and holocephalans) possess paired appendages that project laterally from their gill arches, known as branchial rays. This led Carl Gegenbaur to propose that paired fins (and hence tetrapod limbs) originally evolved via transformation of gill arches. Tetrapod limbs are patterned by asonic hedgehog(Shh)-expressing signalling centre known as the zone of polarising activity, which establishes the anteroposterior axis of the limb bud and maintains proliferative expansion of limb endoskeletal progenitors. Here, we use loss-of-function, label-retention and fate-mapping approaches in the little skate to demonstrate that Shh secretion from a signalling centre in the developing gill arches establishes gill arch anteroposterior polarity and maintains the proliferative expansion of branchial ray endoskeletal progenitor cells. These findings highlight striking parallels in the axial patterning mechanisms employed by chondrichthyan branchial rays and paired fins/limbs, and provide mechanistic insight into the anatomical foundation of Gegenbaur's gill arch hypothesis.This research was supported by a Royal Society University Research Fellowship [UF130182 to JAG], by Plum foundation John E. Dowling and Laura and Arthur Colwin Endowed Summer Research Fellowships at the Marine Biological Laboratory to JAG, by a grant from the University of Cambridge Isaac Newton Trust to [14.23z to JAG], and by a grant from the Natural Sciences and Engineering Research Council of Canada [A5056 to BKH].This is the final version of the article. It first appeared from The Company of Biologists via http://dx.doi.org/10.1242/dev.13388

No health without mental health: Establishing psychiatry as a major discipline in an African Faculty of Health Sciences

Psychiatry has not always been a major clinical discipline in medical schools. Although the Faculty of Health Sciences of the University of Cape Town (UCT) celebrates its Centenary in 2012, a closely aligned major psychiatric hospital is older than the Medical School, while the Department of Psychiatry is only 50 years old. These differing dates reflect the history of and challenge for psychiatry; mental disorders contribute a major portion of the burden of disease, while appropriate recognition and resourcing of services and training has been delayed. There are ongoing challenges in aligning the visions of an old state-run system that focused on those with severe psychotic illness, a newer governmental vision of the importance of treating mental disorders in the community, the realities of current under-resourcing, and the international aspiration that psychiatry is one of the clinical neurosciences. Nevertheless, considerable strides have been made towards moving psychiatry from the periphery of society and medicine to a central discipline within the Faculty of Health Sciences at UCT

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

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

A Guide to the Brain Initiative Cell Census Network Data Ecosystem

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain

An ancient dental gene network regulates development and continuous regeneration of teeth in sharks

The appearance of toothed vertebrates has proven a major determinant of the overall success of this lineage. This is most apparent in sharks and rays (elasmobranchs), which further retain the capacity for life-long tooth regeneration. Given their comparatively basal phylogenetic position, elasmobranchs therefore offer the opportunity for crucial insights into putative ancestral characters of tooth development, yet despite their evolutionary significance this remains poorly understood. Using the established chondrichthyan model, the catshark (Scyliorhinus sp.), we identified the expression of genes representative of conserved signaling pathways during stages of early dental competence, tooth initiation and regeneration. The expression patterns of β-catenin, shh, bmp4, pax9, pitx1/2, and the stem cell marker Sox2, characterise an ancestrally conserved gene set deployed during initiation of the elasmobranch dentition, suggesting that all vertebrate dentitions are defined by the expression of this core set of genes. These findings provide novel evidence to support the conservation in deep evolutionary time of a core set of dental patterning genes, therefore further defining the evolutionary trajectory of tooth development. We show how these genes facilitate the emergence of the shark dentition and offer insights into their deployment during development of the dental lamina, a sheet of dental epithelial cells that are responsible for continuous tooth regeneration. This study further promotes a specific experimental agenda to further characterise the roles of these core developmental genes during vertebrate tooth development, and importantly dental regeneration

Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks