TLR7-mediated skin inflammation remotely triggers chemokine expression and leukocyte accumulation in the brain

Background: The relationship between the brain and the immune system has become increasingly topical as, although it is immune-specialised, the CNS is not free from the influences of the immune system. Recent data indicate that peripheral immune stimulation can significantly affect the CNS. But the mechanisms underpinning this relationship remain unclear. The standard approach to understanding this relationship has relied on systemic immune activation using bacterial components, finding that immune mediators, such as cytokines, can have a significant effect on brain function and behaviour. More rarely have studies used disease models that are representative of human disorders. Methods: Here we use a well-characterised animal model of psoriasis-like skin inflammation—imiquimod—to investigate the effects of tissue-specific peripheral inflammation on the brain. We used full genome array, flow cytometry analysis of immune cell infiltration, doublecortin staining for neural precursor cells and a behavioural read-out exploiting natural burrowing behaviour. Results: We found that a number of genes are upregulated in the brain following treatment, amongst which is a subset of inflammatory chemokines (CCL3, CCL5, CCL9, CXCL10, CXCL13, CXCL16 and CCR5). Strikingly, this model induced the infiltration of a number of immune cell subsets into the brain parenchyma, including T cells, NK cells and myeloid cells, along with a reduction in neurogenesis and a suppression of burrowing activity. Conclusions: These findings demonstrate that cutaneous, peripheral immune stimulation is associated with significant leukocyte infiltration into the brain and suggest that chemokines may be amongst the key mediators driving this response

A One Health overview, facilitating advances in comparative medicine and translational research.

Table of contentsA1 One health advances and successes in comparative medicine and translational researchCheryl StroudA2 Dendritic cell-targeted gorilla adenoviral vector for cancer vaccination for canine melanomaIgor Dmitriev, Elena Kashentseva, Jeffrey N. Bryan, David T. CurielA3 Viroimmunotherapy for malignant melanoma in the companion dog modelJeffrey N. Bryan, David Curiel, Igor Dmitriev, Elena Kashentseva, Hans Rindt, Carol Reinero, Carolyn J. HenryA4 Of mice and men (and dogs!): development of a commercially licensed xenogeneic DNA vaccine for companion animals with malignant melanomaPhilip J. BergmanA5 Successful immunotherapy with a recombinant HER2-expressing Listeria monocytogenes in dogs with spontaneous osteosarcoma paves the way for advances in pediatric osteosarcomaNicola J. Mason, Josephine S. Gnanandarajah, Julie B. Engiles, Falon Gray, Danielle Laughlin, Anita Gaurnier-Hausser, Anu Wallecha, Margie Huebner, Yvonne PatersonA6 Human clinical development of ADXS-HER2Daniel O'ConnorA7 Leveraging use of data for both human and veterinary benefitLaura S. TremlA8 Biologic replacement of the knee: innovations and early clinical resultsJames P. StannardA9 Mizzou BioJoint Center: a translational success storyJames L. CookA10 University and industry translational partnership: from the lab to commercializationMarc JacobsA11 Beyond docking: an evolutionarily guided OneHealth approach to drug discoveryGerald J. Wyckoff, Lee Likins, Ubadah Sabbagh, Andrew SkaffA12 Challenges and opportunities for data applications in animal health: from precision medicine to precision husbandryAmado S. GuloyA13 A cloud-based programmable platform for healthHarlen D. HaysA14 Comparative oncology: One Health in actionAmy K. LeBlancA15 Companion animal diseases bridge the translational gap for human neurodegenerative diseaseJoan R. Coates, Martin L. Katz, Leslie A. Lyons, Gayle C. Johnson, Gary S. Johnson, Dennis P. O'BrienA16 Duchenne muscular dystrophy gene therapyDongsheng DuanA17 Polycystic kidney disease: cellular mechanisms to emerging therapiesJames P. CalvetA18 The domestic cat as a large animal model for polycystic kidney diseaseLeslie A. Lyons, Barbara GandolfiA19 The support of basic and clinical research by the Polycystic Kidney Disease FoundationDavid A. BaronA20 Using naturally occurring large animal models of human disease to enable clinical translation: treatment of arthritis using autologous stromal vascular fraction in dogsMark L. WeissA21 Regulatory requirements regarding clinical use of human cells, tissues, and tissue-based productsDebra A. WebsterA22 Regenerative medicine approaches to Type 1 diabetes treatmentFrancis N. KaranuA23 The zoobiquity of canine diabetes mellitus, man's best friend is a friend indeed-islet transplantationEdward J. RobbA24 One Medicine: a development model for cellular therapy of diabetesRobert J. Harman

A Conserved Mechanism for Sulfonucleotide Reduction

Sulfonucleotide reductases are a diverse family of enzymes that catalyze the first committed step of reductive sulfur assimilation. In this reaction, activated sulfate in the context of adenosine-5′-phosphosulfate (APS) or 3′-phosphoadenosine 5′-phosphosulfate (PAPS) is converted to sulfite with reducing equivalents from thioredoxin. The sulfite generated in this reaction is utilized in bacteria and plants for the eventual production of essential biomolecules such as cysteine and coenzyme A. Humans do not possess a homologous metabolic pathway, and thus, these enzymes represent attractive targets for therapeutic intervention. Here we studied the mechanism of sulfonucleotide reduction by APS reductase from the human pathogen Mycobacterium tuberculosis, using a combination of mass spectrometry and biochemical approaches. The results support the hypothesis of a two-step mechanism in which the sulfonucleotide first undergoes rapid nucleophilic attack to form an enzyme-thiosulfonate (E-Cys-S-SO(3) (−)) intermediate. Sulfite is then released in a thioredoxin-dependent manner. Other sulfonucleotide reductases from structurally divergent subclasses appear to use the same mechanism, suggesting that this family of enzymes has evolved from a common ancestor

Integrating plant physiology into simulation of fire behavior and effects

Wildfires are a global crisis, but current fire models fail to capture vegetation response to changing climate. With drought and elevated temperature increasing the importance of vegetation dynamics to fire behavior, and the advent of next generation models capable of capturing increasingly complex physical processes, we provide a renewed focus on representation of woody vegetation in fire models. Currently, the most advanced representations of fire behavior and biophysical fire effects are found in distinct classes of fine-scale models and do not capture variation in live fuel (i.e. living plant) properties. We demonstrate that plant water and carbon dynamics, which influence combustion and heat transfer into the plant and often dictate plant survival, provide the mechanistic linkage between fire behavior and effects. Our conceptual framework linking remotely sensed estimates of plant water and carbon to fine-scale models of fire behavior and effects could be a critical first step toward improving the fidelity of the coarse scale models that are now relied upon for global fire forecasting. This process-based approach will be essential to capturing the influence of physiological responses to drought and warming on live fuel conditions, strengthening the science needed to guide fire managers in an uncertain future

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

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

Estimating Influenza Hospitalizations among Children

Two surveillance systems gave a better estimate of influenza hospitalizations in children <5 years of age than either system alone

The effectiveness of an intervention in increasing community health clinician provision of preventive care: a study protocol of a non-randomised, multiple-baseline trial

<p>Abstract</p> <p>Background</p> <p>The primary behavioural risks for the most common causes of mortality and morbidity in developed countries are tobacco smoking, poor nutrition, risky alcohol use, and physical inactivity. Evidence, guidelines and policies support routine clinician delivery of care to prevent these risks within primary care settings. Despite the potential afforded by community health services for the delivery of such preventive care, the limited evidence available suggests it is provided at suboptimal levels. This study aims to assess the effectiveness of a multi-strategic practice change intervention in increasing clinician's routine provision of preventive care across a network of community health services.</p> <p>Methods/Design</p> <p>A multiple baseline study will be conducted involving all 56 community health facilities in a single health district in New South Wales, Australia. The facilities will be allocated to one of three administratively-defined groups. A 12 month practice change intervention will be implemented in all facilities in each group to facilitate clinician risk assessment of eligible clients, and clinician provision of brief advice and referral to those identified as being 'at risk'. The intervention will be implemented in a non-random sequence across the three facility groups. Repeated, cross-sectional measurement of clinician provision of preventive care for four individual risks (smoking, poor nutrition, risky alcohol use, and physical inactivity) will occur continuously for all three facility groups for 54 months via telephone interviews. The interviews will be conducted with randomly selected clients who have visited a community health facility in the last two weeks. Data collection will commence 12 months prior to the implementation of the intervention in the first group, and continue for six months following the completion of the intervention in the last group. As a secondary source of data, telephone interviews will be undertaken prior to and following the intervention with randomly selected samples of clinicians from each facility group to assess the reported provision of preventive care, and the acceptability of the practice change intervention and implementation.</p> <p>Discussion</p> <p>The study will provide novel evidence regarding the ability to increase clinician's routine provision of preventive care across a network of community health facilities.</p> <p>Trial registration</p> <p>Australian Clinical Trials Registry <a href="http://www.anzctr.org.au/ACTRN12611001284954.aspx">ACTRN12611001284954</a></p> <p>Universal Trial Number (UTN)</p> <p>U1111-1126-3465</p