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Galea S, Vaughan RD
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Population Health Science as the Basic Science of Public Health: A Public Health of Consequence, October 2018

Chan CS, Laddha SV, Lewis PW, Koletsky MS, Robzyk K, Da Silva E, Torres PJ, Untch BR, Li J, Bose P, Chan TA, Klimstra DS, Allis CD, Tang LH
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ATRX, DAXX or MEN1 mutant pancreatic neuroendocrine tumors are a distinct alpha-cell signature subgroup

NATURE COMMUNICATIONS 2018 OCT 12; 9(?):? Article 4158
The commonly mutated genes in pancreatic neuroendocrine tumors (PanNETs) are ATRX, DAXX, and MEN1. We genotyped 64 PanNETs and found 58% carry ATRX, DAXX, and MEN1 mutations (A-D-M mutant PanNETs) and this correlates with a worse clinical outcome than tumors carrying the wild-type alleles of all three genes (A-D-M WT PanNETs). We performed RNA sequencing and DNA-methylation analysis to reveal two distinct subgroups with one consisting entirely of A-D-M mutant PanNETs. Two genes differentiating A-D-M mutant from A-D-M WT PanNETs were high ARX and low PDX1 gene expression with PDX1 promoter hyper-methylation in the A-D-M mutant PanNETs. Moreover, A-D-M mutant PanNETs had a gene expression signature related to that of alpha-cells (FDR q-value < 0.009) of pancreatic islets including increased expression of HNF1A and its transcriptional target genes. This gene expression profile suggests that A-D-M mutant PanNETs originate from or transdifferentiate into a distinct cell type similar to alpha cells.
Knorr DA, Dahan R, Ravetch JV
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Toxicity of an Fc-engineered anti-CD40 antibody is abrogated by intratumoral injection and results in durable antitumor immunity

Immune stimulation has emerged as a promising approach to the treatment of neoplastic diseases. Currently approved therapeutics, such as anti-CTLA4 and anti-PD1, are primarily aimed at blocking inhibitory signaling by immune cells. An alternative and potentially synergistic approach would involve activation of immune pathways by agonism of stimulatory receptors, such as CD40. Agonistic antibodies, while promising in principle, have encountered significant barriers in clinical trials limited by the systemic toxicity of such approaches. Using a mouse model humanized for both Fc receptors and CD40, we previously demonstrated enhanced antitumor activity with an Fc-modified antibody. We now demonstrate that this model recapitulates the platelet and hepatic toxicities seen with anti-CD40 antibodies in patients, providing a predictive measure of the dose-limiting activity of this approach. We further show that such toxicity can be circumvented and durable systemic antitumor immunity achieved by intratumoral delivery of an Fc-engineered anti-CD40 agonistic antibody.
Inoue K, Deng ZH, Chen YF, Giannopoulou E, Xu R, Gong SC, Greenblatt MB, Mangala LS, Lopez-Berestein G, Kirsch DG, Sood AK, Zhao L, Zhao BH
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Bone protection by inhibition of microRNA-182

NATURE COMMUNICATIONS 2018 OCT 5; 9(?):? Article 4108
Targeting microRNAs recently shows significant therapeutic promise; however, such progress is underdeveloped in treatment of skeletal diseases with osteolysis, such as osteoporosis and rheumatoid arthritis (RA). Here, we identified miR-182 as a key osteoclastogenic regulator in bone homeostasis and diseases. Myeloid-specific deletion of miR-182 protects mice against excessive osteoclastogenesis and bone resorption in disease models of ovariectomy-induced osteoporosis and inflammatory arthritis. Pharmacological treatment of these diseases with miR-182 inhibitors completely suppresses pathologic bone erosion. Mechanistically, we identify protein kinase double-stranded RNA-dependent (PKR) as a new and essential miR-182 target that is a novel inhibitor of osteoclastogenesis via regulation of the endogenous interferon (IFN)-beta-mediated autocrine feedback loop. The expression levels of miR-182, PKR, and IFN-beta are altered in RA and are significantly correlated with the osteoclastogenic capacity of RA monocytes. Our findings reveal a previously unrecognized regulatory network mediated by miR-182-PKR-IFN-beta axis in osteoclastogenesis, and highlight the therapeutic implications of miR-182 inhibition in osteoprotection.
Milham MP, Ai L, Koo B, Xu T, Amiez C, Balezeau F, Baxter MG, Blezer ELA, Brochier T, Chen AH, Croxson PL, Damatac CG, Dehaene S, Everling S, Fair DA, Fleysher L, Freiwald W, Froudist-Walsh S, Griffiths TD, Guedj C, Hadj-Bouziane F, Ben Hamed S, Harel N, Hiba B, Jarraya B, Jung B, Kastner S, Klink PC, Kwok SC, Laland KN, Leopold DA, Lindenfors P, Mars RB, Menon RS, Messinger A, Meunier M, Mok K, Morrison JH, Nacef J, Nagy J, Rios MO, Petkov CI, Pinsk M, Poirier C, Procyk E, Rajimehr R, Reader SM, Roelfsema PR, Rudko DA, Rushworth MFS, Russ BE, Sallet J, Schmid MC, Schwiedrzik CM, Seidlitz J, Sein J, Shmuel A, Sullivan EL, Ungerleider L, Thiele A, Todorov OS, Tsao D, Wang Z, Wilson CRE, Yacoub E, Ye FQ, Zarco W, Zhou YD, Margulies DS, Schroeder CE
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An Open Resource for Non-human Primate Imaging

NEURON 2018 OCT 10; 100(1):61-74.e2
Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.
Watt K, Newsted D, Voorand E, Gooding RJ, Majewski A, Truesdell P, Yao B, Tuschl T, Renwick N, Craig AW
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MicroRNA-206 suppresses TGF-beta signalling to limit tumor growth and metastasis in lung adenocarcinoma

MicroRNA-206 (miR-206) has demonstrated tumor suppressive effects in a variety of cancers. Numerous studies have identified aberrantly expressed targets of miR-206 that contribute to tumor progression and metastasis, however, the broader gene-networks and pathways regulated by miR-206 remain poorly defined. Here, we have ectopically expressed miR-206 in lung adenocarcinoma cell lines and tumors to identify differentially expressed genes, and study the effects on tumor growth and metastasis. In H1299 tumor xenograft assays, stable expression of miR-206 suppressed both tumor growth and metastasis in mice. Profiling of xenograft tumors using small RNA sequencing and a targeted panel of tumor progression and metastasis-related genes revealed a network of genes involved in TGF-beta signalling that were regulated by miR-206. Among these were the TGFB1 ligand, as well as direct transcriptional targets of Smad3. Other differentially expressed genes included components of the extracellular matrix involved in TGF-beta activation and signalling, including Thrombospondin-1, which is responsible for the activation of latent TGF-beta in the stroma. In cultured lung adenocarcinoma cells treated with recombinant TGF-beta, ectopic expression of miR-206 impaired canonical signalling, and expression of TGF-beta target genes linked to epithelial-mesenchymal transition. This was due at least in part to the suppression of Smad3 protein levels in lung adenocarcinoma cells with ectopic miR-206 expression. Together, these findings indicate that miR-206 can suppress tumor progression and metastasis by limiting autocrine production of TGF-beta, and highlight the potential utility of TGF-beta inhibitors for the treatment of lung adenocarcinomas.
Jacobsen JT, Mesin L, Markoulaki S, Schiepers A, Cavazzoni CB, Bousbaine D, Jaenisch R, Victora GD
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One-step generation of monoclonal B cell receptor mice capable of isotype switching and somatic hypermutation

We developed a method for rapid generation of B cell receptor (BCR) monoclonal mice expressing prerearranged Igh and Igk chains monoallelically from the Igh locus by CRI SPR-Cas9 injection into fertilized oocytes. B cells from these mice undergo somatic hypermutation (SHM), class switch recombination (CSR), and affinity-based selection in germinal centers. This method combines the practicality of BCR transgenes with the ability to study Ig SHM, CSR, and affinity maturation.
Aaltonen T, Amerio S, Amidei D, Anastassov A, Annovi A, Antos J, Apollinari G, Appel JA, Arisawa T, Artikov A, Asaadi J, Ashmanskas W, Auerbach B, Aurisano A, Azfar F, Badgett W, Bae T, Barbaro-Galtieri A, Barnes VE, Barnett BA, Barria P, Bartos P, Bauce M, Bedeschi F, Behari S, Bellettini G, Bellinger J, Benjamin D, Beretvas A, Bhatti A, Bland KR, Blumenfeld B, Bocci A, Bodek A, Bortoletto D, Boudreau J, Boveia A, Brigliadori L, Bromberg C, Brucken E, Budagov J, Budd HS, Burkett K, Busetto G, Bussey P, Butti P, Buzatu A, Calamba A, Camarda S, Campanelli M, Canelli F, Carls B, Carlsmith D, Carosi R, Carrillo S, Casal B, Casarsa M, Castro A, Catastini P, Cauz D, Cavaliere V, Cerri A, Cerrito L, Chen YC, Chertok M, Chiarelli G, Chlachidze G, Cho K, Chokheli D, Clark A, Clarke C, Convery ME, Conway J, Corbo M, Cordelli M, Cox CA, Cox DJ, Cremonesi M, Cruz D, Cuevas J, Culbertson R, d'Ascenzo N, Datta M, de Barbaro P, Demortier L, Deninno M, D'Errico M, Devoto F, Di Canto A, Di Ruzza B, Dittmann JR, Donati S, D'Onofrio M, Dorigo M, Driutti A, Ebina K, Edgar R, Elagin A, Erbacher R, Errede S, Esham B, Farrington S, Ramos JPF, Field R, Flanagan G, Forrest R, Franklin M, Freeman JC, Frisch H, Funakoshi Y, Galloni C, Garfinkel AF, Garosi P, Gerberich H, Gerchtein E, Giagu S, Giakoumopoulou V, Gibson K, Ginsburg CM, Giokaris N, Giromini P, Glagolev V, Glenzinski D, Gold M, Goldin D, Golossanov A, Gomez G, Gomez-Ceballos G, Goncharov M, Lopez OG, Gorelov I, Goshaw AT, Goulianos K, Gramellini E, Grosso-Pilcher C, da Costa JG, Hahn SR, Han JY, Happacher F, Hara K, Hare M, Harr RF, Harrington-Taber T, Hatakeyama K, Hays C, Heinrich J, Herndon M, Hocker A, Hong Z, Hopkins W, Hou S, Hughes RE, Husemann U, Hussein M, Huston J, Introzzi G, Iori M, Ivanov A, James E, Jang D, Jayatilaka B, Jeon EJ, Jindariani S, Jones M, Joo KK, Jun SY, Junk TR, Kambeitz M, Kamon T, Karchin PE, Kasmi A, Kato Y, Ketchum W, Keung J, Kilminster B, Kim DH, Kim HS, Kim JE, Kim MJ, Kim SH, Kim SB, Kim YJ, Kim YK, Kimura N, Kirby M, Kondo K, Kong DJ, Konigsberg J, Kotwal AV, Kreps M, Kroll J, Kruse M, Kuhr T, Kurata M, Laasanen AT, Lammel S, Lancaster M, Lannon K, Latino G, Lee HS, Lee JS, Leo S, Leone S, Lewis JD, Limosani A, Lipeles E, Lister A, Liu Q, Liu T, Lockwitz S, Loginov A, Lucchesi D, Luca A, Lueck J, Lujan P, Lukens P, Lungu G, Lys J, Lysak R, Madrak R, Maestro P, Malik S, Manca G, Manousakis-Katsikakis A, Marchese L, Margaroli F, Marino P, Matera K, Mattson ME, Mazzacane A, Mazzanti P, McNulty R, Mehta A, Mehtala P, Mesropian C, Miao T, Michielin E, Mietlicki D, Mitra A, Miyake H, Moed S, Moggi N, Moon CS, Moore R, Morello MJ, Mukherjee A, Muller T, Murat P, Mussini M, Nachtman J, Nagai Y, Naganoma J, Nakano I, Napier A, Nett J, Nigmanov T, Nodulman L, Noh SY, Norniella O, Oakes L, Oh SH, Oh YD, Okusawa T, Orava R, Ortolan L, Pagliarone C, Palencia E, Palni P, Papadimitriou V, Parker W, Pauletta G, Paulini M, Paus C, Phillips TJ, Piacentino G, Pianori E, Pilot J, Pitts K, Plager C, Pondrom L, Poprocki S, Potamianos K, Pranko A, Prokoshin F, Ptohos F, Punzi G, Fernandez IR, Renton P, Rescigno M, Rimondi F, Ristori L, Robson A, Rodriguez T, Rolli S, Ronzani M, Roser R, Rosner JL, Ruffini F, Ruiz A, Russ J, Rusu V, Sakumoto WK, Sakurai Y, Santi L, Sato K, Saveliev V, Savoy-Navarro A, Schlabach P, Schmidt EE, Schwarz T, Scodellaro L, Scuri F, Seidel S, Seiya Y, Semenov A, Sforza F, Shalhout SZ, Shears T, Shepard PF, Shimojima M, Shochet M, Shreyber-Tecker I, Simonenko A, Sliwa K, Smith JR, Snider FD, Song H, Sorin V, St Denis R, Stancari M, Stentz D, Strologas J, Sudo Y, Sukhanov A, Suslov I, Takemasa K, Takeuchi Y, Tang J, Tecchio M, Teng PK, Thom J, Thomson E, Thukral V, Toback D, Tokar S, Tollefson K, Tomura T, Tonelli D, Torre S, Torretta D, Totaro P, Trovato M, Ukegawa F, Uozumi S, Vazquez F, Velev G, Vellidis C, Vernieri C, Vidal M, Vilar R, Vizan J, Vogel M, Volpi G, Wagner P, Wallny R, Wang SM, Waters D, Wester WC, Whiteson D, Wicklund AB, Wilbur S, Williams HH, Wilson JS, Wilson P, Winer BL, Wittich P, Wolbers S, Wolfmeister H, Wright T, Wu X, Wu Z, Yamamoto K, Yamato D, Yang T, Yang UK, Yang YC, Yao WM, Yeh GP, Yi K, Yoh J, Yorita K, Yoshida T, Yu GB, Yu I, Zanetti AM, Zeng Y, Zhou C, Zucchelli S
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Search for standard-model Z and Higgs bosons decaying into a bottom-antibottom quark pair in proton-antiproton collisions at 1.96 TeV

PHYSICAL REVIEW D 2018 OCT 11; 98(7):? Article 072002
The Collider Detector at Fermilab collected a unique sample of jets originating from bottom-quark fragmentation (b-jets) by selecting online proton-antiproton (p (p) over bar) collisions with a vertex displaced from p (p) over bar interaction point, consistent with the decay of a bottom-quark hadron. This data set, collected at a center-of-mass energy of 1.96 TeV, and corresponding to an integrated luminosity of 5.4 fb(-1), is used to measure the Z-boson production cross section times branching ratio into b (b) over bar. The number of Z -> b (b) over bar events is determined by fitting the dijet-mass distribution, while constraining the dominant b-jet background, originating from QCD multijet events, with data. The result, sigma(p(p)over bar> -> Z) x B(Z -> b (b) over bar) = 1.11 +/- 0.08(stat) +/- 0.14(syst) nb, is the most precise measurement of this process, and is consistent with the standard-model prediction. The data set is also used to search for Higgs-boson production. No significant signal is expected in our data and the first upper limit on the cross section for the inclusive p(p)over bar>-> H -> b (b) over bar process at root s = 1.96 TeV is set, corresponding to 33 times the expected standard-model cross section, or sigma = 40.6 pb, at the 95% confidence level.
Zhou J, Benito-Martin A, Mighty J, Chang L, Ghoroghi S, Wu H, Wong M, Guariglia S, Baranov P, Young M, Gharbaran R, Emerson M, Mark MT, Molina H, Canto-Soler MV, Selgas HP, Redenti S
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Retinal progenitor cells release extracellular vesicles containing developmental transcription factors, microRNA and membrane proteins (vol 8, 2823, 2018)

SCIENTIFIC REPORTS 2018 OCT 22; 8(?):? Article 15801
Auksztulewicz R, Schwiedrzik CM, Thesen T, Doyle W, Devinsky O, Nobre AC, Schroeder CE, Friston KJ, Melloni L
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Not All Predictions Are Equal: "What" and "When " Predictions Modulate Activity in Auditory Cortex through Different Mechanisms

JOURNAL OF NEUROSCIENCE 2018 OCT 3; 38(40):8680-8693
Using predictions based on environmental regularities is fundamental for adaptive behavior. While it is widely accepted that predictions across different stimulus attributes (e.g., time and content) facilitate sensory processing, it is unknown whether predictions across these attributes rely on the same neural mechanism. Here, to elucidate the neural mechanisms of predictions, we combine invasive electrophysiological recordings (human electrocorticography in 4 females and 2 males) with computational modeling while manipulating predictions about content ("what") and time ("when"). We found that "when" predictions increased evoked activity over motor and prefrontal regions both at early (similar to 180 ms) and late (430 - 450 ms) latencies. "What" predictability, however, increased evoked activity only over prefrontal areas late in time (420 - 460 ms). Beyond these dissociable influences, we found that "what" and "when" predictability interactively modulated the amplitude of early (165 ms) evoked responses in the superior temporal gyrus. We modeled the observed neural responses using biophysically realistic neural mass models, to better understand whether "what" and "when" predictions tap into similar or different neurophysiological mechanisms. Our modeling results suggest that "what" and "when" predictability rely on complementary neural processes: "what" predictions increased short-term plasticity in auditory areas, whereas "when" predictability increased synaptic gain in motor areas. Thus, content and temporal predictions engage complementary neural mechanisms in different regions, suggesting domain-specific prediction signaling along the cortical hierarchy. Encoding predictions through different mechanisms may endow the brain with the flexibility to efficiently signal different sources of predictions, weight them by their reliability, and allow for their encoding without mutual interference.