The Concise Guide to PHARMACOLOGY 2015/16:Voltage-gated ion channels

The Concise Guide to PHARMACOLOGY 2015/16 provides concise overviews of the key properties of over 1750 human drug targets with their pharmacology, plus links to an open access knowledgebase of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. The full contents can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.13350/full. Voltage-gated ion channels are one of the eight major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, ligand-gated ion channels, other ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The Concise Guide is published in landscape format in order to facilitate comparison of related targets. It is a condensed version of material contemporary to late 2015, which is presented in greater detail and constantly updated on the website www.guidetopharmacology.org, superseding data presented in the previous Guides to Receptors & Channels and the Concise Guide to PHARMACOLOGY 2013/14. It is produced in conjunction with NC-IUPHAR and provides the official IUPHAR classification and nomenclature for human drug targets, where appropriate. It consolidates information previously curated and displayed separately in IUPHAR-DB and GRAC and provides a permanent, citable, point-in-time record that will survive database updates

The IUPHAR/BPS Guide to PHARMACOLOGY in 2016: towards curated quantitative interactions between 1300 protein targets and 6000 ligands

The IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb, http://www.guidetopharmacology.org) provides expert-curated molecular interactions between successful and potential drugs and their targets in the human genome. Developed by the International Union of Basic and Clinical Pharmacology (IUPHAR) and the British Pharmacological Society (BPS), this resource, and its earlier incarnation as IUPHAR-DB, is described in our 2014 publication. This update incorporates changes over the intervening seven database releases. The unique model of content capture is based on established and new target class subcommittees collaborating with in-house curators. Most information comes from journal articles, but we now also index kinase cross-screening panels. Targets are specified by UniProtKB IDs. Small molecules are defined by PubChem Compound Identifiers (CIDs); ligand capture also includes peptides and clinical antibodies. We have extended the capture of ligands and targets linked via published quantitative binding data (e.g. Ki, IC50 or Kd). The resulting pharmacological relationship network now defines a data-supported druggable genome encompassing 7% of human proteins. The database also provides an expanded substrate for the biennially published compendium, the Concise Guide to PHARMACOLOGY. This article covers content increase, entity analysis, revised curation strategies, new website features and expanded download options

The Concise Guide to Pharmacology 2015/16: Overview

The Concise Guide to PHARMACOLOGY 2015/16 provides concise overviews of the key properties of over 1750 human drug targets with their pharmacology, plus links to an open access knowledgebase of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. The full contents can be found at http://onlinelibrary.wiley.com/doi/10. 1111/bph.13347/full. This compilation of the major pharmacological targets is divided into eight areas of focus: G protein-coupled receptors, ligand-gated ion channels, voltage-gated ion channels, other ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The Concise Guide is published in landscape format in order to facilitate comparison of related targets. It is a condensed version of material contemporary to late 2015, which is presented in greater detail and constantly updated on the website www.guidetopharmacology.org, superseding data presented in the previous Guides to Receptors & Channels and the Concise Guide to PHARMACOLOGY 2013/14. It is produced in conjunction with NC-IUPHAR and provides the official IUPHAR classification and nomenclature for human drug targets, where appropriate. It consolidates information previously curated and displayed separately in IUPHAR-DB and GRAC and provides a permanent, citable, point-in-time record that will survive database update

TIGIT acts as an immune checkpoint upon inhibition of PD1 signaling in autoimmune diabetes

IntroductionChronic activation of self-reactive T cells with beta cell antigens results in the upregulation of immune checkpoint molecules that keep self-reactive T cells under control and delay beta cell destruction in autoimmune diabetes. Inhibiting PD1/PD-L1 signaling results in autoimmune diabetes in mice and humans with pre-existing autoimmunity against beta cells. However, it is not known if other immune checkpoint molecules, such as TIGIT, can also negatively regulate self-reactive T cells. TIGIT negatively regulates the CD226 costimulatory pathway, T-cell receptor (TCR) signaling, and hence T-cell function.MethodsThe phenotype and function of TIGIT expressing islet infiltrating T cells was studied in non-obese diabetic (NOD) mice using flow cytometry and single cell RNA sequencing. To determine if TIGIT restrains self-reactive T cells, we used a TIGIT blocking antibody alone or in combination with anti-PDL1 antibody.ResultsWe show that TIGIT is highly expressed on activated islet infiltrating T cells in NOD mice. We identified a subset of stem-like memory CD8+ T cells expressing multiple immune checkpoints including TIGIT, PD1 and the transcription factor EOMES, which is linked to dysfunctional CD8+ T cells. A known ligand for TIGIT, CD155 was expressed on beta cells and islet infiltrating dendritic cells. However, despite TIGIT and its ligand being expressed, islet infiltrating PD1+TIGIT+CD8+ T cells were functional. Inhibiting TIGIT in NOD mice did not result in exacerbated autoimmune diabetes while inhibiting PD1-PDL1 resulted in rapid autoimmune diabetes, indicating that TIGIT does not restrain islet infiltrating T cells in autoimmune diabetes to the same degree as PD1. Partial inhibition of PD1-PDL1 in combination with TIGIT inhibition resulted in rapid diabetes in NOD mice. DiscussionThese results suggest that TIGIT and PD1 act in synergy as immune checkpoints when PD1 signaling is partially impaired. Beta cell specific stem-like memory T cells retain their functionality despite expressing multiple immune checkpoints and TIGIT is below PD1 in the hierarchy of immune checkpoints in autoimmune diabetes

Measurement of inclusive D*+- and associated dijet cross sections in photoproduction at HERA

Inclusive photoproduction of D*+- mesons has been measured for photon-proton centre-of-mass energies in the range 130 < W < 280 GeV and a photon virtuality Q^2 < 1 GeV^2. The data sample used corresponds to an integrated luminosity of 37 pb^-1. Total and differential cross sections as functions of the D* transverse momentum and pseudorapidity are presented in restricted kinematical regions and the data are compared with next-to-leading order (NLO) perturbative QCD calculations using the "massive charm" and "massless charm" schemes. The measured cross sections are generally above the NLO calculations, in particular in the forward (proton) direction. The large data sample also allows the study of dijet production associated with charm. A significant resolved as well as a direct photon component contribute to the cross section. Leading order QCD Monte Carlo calculations indicate that the resolved contribution arises from a significant charm component in the photon. A massive charm NLO parton level calculation yields lower cross sections compared to the measured results in a kinematic region where the resolved photon contribution is significant.Comment: 32 pages including 6 figure

Measurement of Jet Shapes in Photoproduction at HERA

The shape of jets produced in quasi-real photon-proton collisions at centre-of-mass energies in the range $134-277$ GeV has been measured using the hadronic energy flow. The measurement was done with the ZEUS detector at HERA. Jets are identified using a cone algorithm in the $\eta - \phi$ plane with a cone radius of one unit. Measured jet shapes both in inclusive jet and dijet production with transverse energies $E^{jet}_T>14$ GeV are presented. The jet shape broadens as the jet pseudorapidity ($\eta^{jet}$) increases and narrows as $E^{jet}_T$ increases. In dijet photoproduction, the jet shapes have been measured separately for samples dominated by resolved and by direct processes. Leading-logarithm parton-shower Monte Carlo calculations of resolved and direct processes describe well the measured jet shapes except for the inclusive production of jets with high $\eta^{jet}$ and low $E^{jet}_T$. The observed broadening of the jet shape as $\eta^{jet}$ increases is consistent with the predicted increase in the fraction of final state gluon jets.Comment: 29 pages including 9 figure

The Concise Guide to PHARMACOLOGY 2015/16: Overview

The Concise Guide to PHARMACOLOGY 2015/16 provides concise overviews of the key properties of over 1750 human drug targets with their pharmacology, plus links to an open access knowledgebase of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. The full contents can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.13347/full. This compilation of the major pharmacological targets is divided into eight areas of focus: G protein-coupled receptors, ligand-gated ion channels, voltage-gated ion channels, other ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The Concise Guide is published in landscape format in order to facilitate comparison of related targets. It is a condensed version of material contemporary to late 2015, which is presented in greater detail and constantly updated on the website www.guidetopharmacology.org, superseding data presented in the previous Guides to Receptors & Channels and the Concise Guide to PHARMACOLOGY 2013/14. It is produced in conjunction with NC-IUPHAR and provides the official IUPHAR classification and nomenclature for human drug targets, where appropriate. It consolidates information previously curated and displayed separately in IUPHAR-DB and GRAC and provides a permanent, citable, point-in-time record that will survive database updates.We are extremely grateful for the financial contributions from the British Pharmacological Society, the International Union of Basic and Clinical Pharmacology, the Wellcome Trust (099156/Z/12/Z]), which support the website

Measurement of the Diffractive Cross Section in Deep Inelastic Scattering using ZEUS 1994 Data

The DIS diffractive cross section, $d\sigma^{diff}_{\gamma^* p \to XN}/dM_X$, has been measured in the mass range $M_X < 15$ GeV for $\gamma^*p$ c.m. energies $60 < W < 200$ GeV and photon virtualities $Q^2 = 7$ to 140 GeV$^2$. For fixed $Q^2$ and $M_X$, the diffractive cross section rises rapidly with $W$, $d\sigma^{diff}_{\gamma^*p \to XN}(M_X,W,Q^2)/dM_X \propto W^{a^{diff}}$ with $a^{diff} = 0.507 \pm 0.034 (stat)^{+0.155}_{-0.046}(syst)$ corresponding to a $t$-averaged pomeron trajectory of \bar{\alphapom} = 1.127 \pm 0.009 (stat)^{+0.039}_{-0.012} (syst) which is larger than \bar{\alphapom} observed in hadron-hadron scattering. The $W$ dependence of the diffractive cross section is found to be the same as that of the total cross section for scattering of virtual photons on protons. The data are consistent with the assumption that the diffractive structure function $F^{D(3)}_2$ factorizes according to \xpom F^{D(3)}_2 (\xpom,\beta,Q^2) = (x_0/ \xpom)^n F^{D(2)}_2(\beta,Q^2). They are also consistent with QCD based models which incorporate factorization breaking. The rise of \xpom F^{D(3)}_2 with decreasing \xpom and the weak dependence of $F^{D(2)}_2$ on $Q^2$ suggest a substantial contribution from partonic interactions

Measurement of the F2 structure function in deep inelastic e+^{+}p scattering using 1994 data from the ZEUS detector at HERA

We present measurements of the structure function \Ft\ in e^+p scattering at HERA in the range 3.5\;\Gevsq < \qsd < 5000\;\Gevsq. A new reconstruction method has allowed a significant improvement in the resolution of the kinematic variables and an extension of the kinematic region covered by the experiment. At \qsd < 35 \;\Gevsq the range in x now spans 6.3\cdot 10^{-5} < x < 0.08 providing overlap with measurements from fixed target experiments. At values of Q^2 above 1000 GeV^2 the x range extends to 0.5. Systematic errors below 5\perc\ have been achieved for most of the kinematic urray, W

Procalcitonin Is Not a Reliable Biomarker of Bacterial Coinfection in People With Coronavirus Disease 2019 Undergoing Microbiological Investigation at the Time of Hospital Admission

Abstract Admission procalcitonin measurements and microbiology results were available for 1040 hospitalized adults with coronavirus disease 2019 (from 48 902 included in the International Severe Acute Respiratory and Emerging Infections Consortium World Health Organization Clinical Characterisation Protocol UK study). Although procalcitonin was higher in bacterial coinfection, this was neither clinically significant (median [IQR], 0.33 [0.11–1.70] ng/mL vs 0.24 [0.10–0.90] ng/mL) nor diagnostically useful (area under the receiver operating characteristic curve, 0.56 [95% confidence interval, .51–.60]).</jats:p