Antiinflammatory and Analgesic Transdermal Gel
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Comparing the Effects of Salts of Diclofenac and Almioprofen with Aspirin on Serum Electrolytes, Creatinine and Urea Levels in Rabbits
Comparing the effects of salts of diclofenac and almioprofen with aspirin on serum electrolytes, creatinine and urea levels in rabbits Nawazish-i-Husain Syed*, Farnaz Zehra, Amir Ali Rizvi Syed, Sabiha Karim and Farrakh Zia Khan University College of Pharmacy, University of the Punjab, Lahore, Pakistan Abstract: The effects of diclofenac sodium, diclofenac potassium, alminoprofen and aspirin on serum electrolytes (serum Na+ and K+), urea and creatinine were compared in rabbits in acute and chronic phases of treatment. The data suggested that all the four drugs markedly increased the serum electrolytes, urea and creatinine levels in both post- treatment phases. In conclusion, present study does not present any advantage of diclofenac sodium over diclofenac potassium at electrolyte levels on short and long term treatment. Nevertheless, current data support the evidence of renal function impairment by all the four drug therapies used in the present study, which is generally caused by NSAIDS. Keywords: NSAIDs, renal function, serum electrolytes. INTRODUCTION were given fodder twice daily, while water was available ad libitum. Throughout the study, environmental Inflammatory diseases including rheumatoid arthritis and conditions remained constant. Rabbits were divided into osteoarthritis are initially treated with non-steroidal anti- five groups, each of six animals. Same group of animals inflammatory drugs (NSAIDS) (Patrono and Rocca, were used for acute and chronic phases of the study. In 2009). Previously, steroids were prescribed to manage the both studies, rabbits of each group were orally chronic inflammatory diseases, however, due to their administered diclofenac Na+, diclofenac K+, severe adverse effects, NSAIDS has become the first alminoprofen, acetyl salicylic acid in a doses of 2.5mg, choice to treat these diseases. -
Table S1: Sensitivity, Specificity, PPV, NPV, and F1 Score of NLP Vs. ICD for Identification of Symptoms for (A) Biome Developm
Table S1: Sensitivity, specificity, PPV, NPV, and F1 score of NLP vs. ICD for identification of symptoms for (A) BioMe development cohort; (B) BioMe validation cohort; (C) MIMIC-III; (D) 1 year of notes from patients in BioMe calculated using manual chart review. A) Fatigue Nausea and/or vomiting Anxiety Depression NLP (95% ICD (95% CI) P NLP (95% CI) ICD (95% CI) P NLP (95% CI) ICD (95% CI) P NLP (95% CI) ICD (95% CI) P CI) 0.99 (0.93- 0.59 (0.43- <0.00 0.25 (0.12- <0.00 <0.00 0.54 (0.33- Sensitivity 0.99 (0.9 – 1) 0.98 (0.88 -1) 0.3 (0.15-0.5) 0.85 (0.65-96) 0.02 1) 0.73) 1 0.42) 1 1 0.73) 0.57 (0.29- 0.9 (0.68- Specificity 0.89 (0.4-1) 0.75 (0.19-1) 0.68 0.97 (0.77-1) 0.03 0.98 (0.83-1) 0.22 0.81 (0.53-0.9) 0.96 (0.79-1) 0.06 0.82) 0.99) 0.99 (0.92- 0.86 (0.71- 0.94 (0.79- 0.79 (0.59- PPV 0.96 (0.82-1) 0.3 0.95 (0.66-1) 0.02 0.95 (0.66-1) 0.16 0.93 (0.68-1) 0.12 1) 0.95) 0.99) 0.92) 0.13 (0.03- <0.00 0.49 (0.33- <0.00 0.66 (0.48- NPV 0.89 (0.4-1) 0.007 0.94 (0.63-1) 0.34 (0.2-0.51) 0.97 (0.81-1) 0.86 (0.6-0.95) 0.04 0.35) 1 0.65) 1 0.81) <0.00 <0.00 <0.00 F1 Score 0.99 0.83 0.88 0.57 0.95 0.63 0.82 0.79 0.002 1 1 1 Itching Cramp Pain NLP (95% ICD (95% CI) P NLP (95% CI) ICD (95% CI) P NLP (95% CI) ICD (95% CI) P CI) 0.98 (0.86- 0.24 (0.09- <0.00 0.09 (0.01- <0.00 0.52 (0.37- <0.00 Sensitivity 0.98 (0.85-1) 0.99 (0.93-1) 1) 0.45) 1 0.29) 1 0.66) 1 0.89 (0.72- 0.5 (0.37- Specificity 0.96 (0.8-1) 0.98 (0.86-1) 0.68 0.98 (0.88-1) 0.18 0.5 (0-1) 1 0.98) 0.66) 0.88 (0.69- PPV 0.96 (0.8-1) 0.8 (0.54-1) 0.32 0.8 (0.16-1) 0.22 0.99 (0.93-1) 0.98 (0.87-1) NA* 0.97) 0.98 (0.85- 0.57 (0.41- <0.00 0.58 (0.43- <0.00 NPV 0.98 (0.86-1) 0.5 (0-1) 0.02 (0-0.08) NA* 1) 0.72) 1 0.72) 1 <0.00 <0.00 <0.00 F1 Score 0.97 0.56 0.91 0.28 0.99 0.68 1 1 1 *Denotes 95% confidence intervals and P values that could not be calculated due to insufficient cells in 2x2 tables. -
What Are the Acute Treatments for Migraine and How Are They Used?
2. Acute Treatment CQ II-2-1 What are the acute treatments for migraine and how are they used? Recommendation The mainstay of acute treatment for migraine is pharmacotherapy. The drugs used include (1) acetaminophen, (2) non-steroidal anti-inflammatory drugs (NSAIDs), (3) ergotamines, (4) triptans and (5) antiemetics. Stratified treatment according to the severity of migraine is recommended: use NSAIDs such as aspirin and naproxen for mild to moderate headache, and use triptans for moderate to severe headache, or even mild to moderate headache when NSAIDs were ineffective in the past. It is necessary to give guidance and cautions to patients having acute attacks, and explain the methods of using medications (timing, dose, frequency of use) and medication use during pregnancy and breast-feeding. Grade A Background and Objective The objective of acute treatment is to resolve the migraine attack completely and rapidly and restore the patient’s normal functions. An ideal treatment should have the following characteristics: (1) resolves pain and associated symptoms rapidly; (2) is consistently effective; (3) no recurrence; (4) no need for additional use of medication; (5) no adverse effects; (6) can be administered by the patients themselves; and (7) low cost. Literature was searched to identify acute treatments that satisfy the above conditions. Comments and Evidence The acute treatment drugs for migraine generally include (1) acetaminophens, (2) non-steroidal anti-inflammatory drugs (NSAIDs), (3) ergotamines, (4) triptans, and (5) antiemetics. For severe migraines including status migrainosus and migraine attacks refractory to treatment, (6) anesthetics, and (7) corticosteroids (dexamethasone) are used (Tables 1 and 2).1)-9) There are two approaches to the selection and sequencing of these medications: “step care” and “stratified care”. -
Horsemen's Information 2016和文TGP 1 薬物修正後 E
[Conditions] 1 Date December 29 (Tue), 2020 2020 Oi Racetrack, Race 10 2 Location TCK, Oi Racetrack 3 Race The 66th Running of Tokyo Daishoten (GI) 4 Eligibility Thoroughbreds, 3 years old & up 5 Full Gate 16 horses 6 Foreign Runners Selected by the selection committee from among the pre-entered horses. 7 Distance 2,000m, 1 1/4 mile (Right-handed, dirt course) 8 Weight 3 years old: 121.5 lbs,4 years old & up: 125.5 lbs, Female: 4.4 lbs less For 3 year-old-horses from the southern hemisphere, reduce 4.4 lbs from the above weight. 9 Purse Unit: 1,000 JPY Prize Purse & Bonus money Running Record 1st place 6th place allowances prize *1 prize *2 1st place 2nd place 3rd place 4th place 5th place or lower Owner 80,000 28,000 16,000 8,000 4,000 300 300 50 1,600 Trainer 880 70 60 50 40 30 30 80 Jockey 120 110 100 80 70 60 30 80 Groom 80 70 60 50 40 30 30 80 Rider 30 30 80 *1 Paid for the runner who broke the previous record and also set the best record during the race. *2 Prize equivalent to the amount listed in the table above is presented. *3 1 USD= 105.88 JPY (As of August,2020) 10 Handling of Late Scratch No allowance is paid in the case of a late scratch (including cancelation of race due to standstill in a starting gate) approved by TCK, Stewards, and Starter. However, if the chairman of the race meeting operation committee deems that the horse is involved in an accident not caused by the horse, the owner is given an running allowance. -
Health Reports for Mutual Recognition of Medical Prescriptions: State of Play
The information and views set out in this report are those of the author(s) and do not necessarily reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein. Executive Agency for Health and Consumers Health Reports for Mutual Recognition of Medical Prescriptions: State of Play 24 January 2012 Final Report Health Reports for Mutual Recognition of Medical Prescriptions: State of Play Acknowledgements Matrix Insight Ltd would like to thank everyone who has contributed to this research. We are especially grateful to the following institutions for their support throughout the study: the Pharmaceutical Group of the European Union (PGEU) including their national member associations in Denmark, France, Germany, Greece, the Netherlands, Poland and the United Kingdom; the European Medical Association (EMANET); the Observatoire Social Européen (OSE); and The Netherlands Institute for Health Service Research (NIVEL). For questions about the report, please contact Dr Gabriele Birnberg ([email protected] ). Matrix Insight | 24 January 2012 2 Health Reports for Mutual Recognition of Medical Prescriptions: State of Play Executive Summary This study has been carried out in the context of Directive 2011/24/EU of the European Parliament and of the Council of 9 March 2011 on the application of patients’ rights in cross- border healthcare (CBHC). The CBHC Directive stipulates that the European Commission shall adopt measures to facilitate the recognition of prescriptions issued in another Member State (Article 11). At the time of submission of this report, the European Commission was preparing an impact assessment with regards to these measures, designed to help implement Article 11. -
The Involvement of Endoplasmic Reticulum Stress in the Suppression of Colorectal Tumorigenesis by Tolfenamic Acid
Published OnlineFirst October 8, 2013; DOI: 10.1158/1940-6207.CAPR-13-0220 Cancer Prevention Research Article Research The Involvement of Endoplasmic Reticulum Stress in the Suppression of Colorectal Tumorigenesis by Tolfenamic Acid Xiaobo Zhang1,2, Seong-Ho Lee3, Kyung-Won Min2, Michael F. McEntee2, Jin Boo Jeong3, Qingwang Li1, and Seung Joon Baek2 Abstract The nonsteroidal anti-inflammatory drug tolfenamic acid has been shown to suppress cancer cell growth and tumorigenesis in different cancer models. However, the underlying mechanism by which tolfenamic acid exerts its antitumorigenic effect remains unclear. Previous data from our group and others indicate that tolfenamic acid alters expression of apoptosis- and cell-cycle arrest–related genes in colorectal cancer cells. þ Here, we show that tolfenamic acid markedly reduced the number of polyps and tumor load in APCmin/ mice, accompanied with cyclin D1 downregulation in vitro and in vivo. Mechanistically, tolfenamic acid promotes endoplasmic reticulum (ER) stress, resulting in activation of the unfolded protein response (UPR) signaling pathway, of which PERK-mediated phosphorylation of eukaryotic translation initiation factor 2a (eIF2a) induces the repression of cyclin D1 translation. Moreover, the PERK-eIF2a-ATF4 branch of the UPR pathway plays a role in tolfenamic acid-induced apoptosis in colorectal cancer cells, as silencing ATF4 attenuates tolfenamic acid-induced apoptosis. Taken together, these results suggest ER stress is involved in tolfenamic acid-induced inhibition of colorectal cancer cell growth, which could contribute to antitumor- igenesis in a mouse model. Cancer Prev Res; 6(12); 1–11. Ó2013 AACR. Introduction and has received much attention since the inhibition of Colorectal cancer is the third-leading cause of cancer- COX-2 activity produces adverse effects (5). -
4 Supplementary File
Supplemental Material for High-throughput screening discovers anti-fibrotic properties of Haloperidol by hindering myofibroblast activation Michael Rehman1, Simone Vodret1, Luca Braga2, Corrado Guarnaccia3, Fulvio Celsi4, Giulia Rossetti5, Valentina Martinelli2, Tiziana Battini1, Carlin Long2, Kristina Vukusic1, Tea Kocijan1, Chiara Collesi2,6, Nadja Ring1, Natasa Skoko3, Mauro Giacca2,6, Giannino Del Sal7,8, Marco Confalonieri6, Marcello Raspa9, Alessandro Marcello10, Michael P. Myers11, Sergio Crovella3, Paolo Carloni5, Serena Zacchigna1,6 1Cardiovascular Biology, 2Molecular Medicine, 3Biotechnology Development, 10Molecular Virology, and 11Protein Networks Laboratories, International Centre for Genetic Engineering and Biotechnology (ICGEB), Padriciano, 34149, Trieste, Italy 4Institute for Maternal and Child Health, IRCCS "Burlo Garofolo", Trieste, Italy 5Computational Biomedicine Section, Institute of Advanced Simulation IAS-5 and Institute of Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany 6Department of Medical, Surgical and Health Sciences, University of Trieste, 34149 Trieste, Italy 7National Laboratory CIB, Area Science Park Padriciano, Trieste, 34149, Italy 8Department of Life Sciences, University of Trieste, Trieste, 34127, Italy 9Consiglio Nazionale delle Ricerche (IBCN), CNR-Campus International Development (EMMA- INFRAFRONTIER-IMPC), Rome, Italy This PDF file includes: Supplementary Methods Supplementary References Supplementary Figures with legends 1 – 18 Supplementary Tables with legends 1 – 5 Supplementary Movie legends 1, 2 Supplementary Methods Cell culture Primary murine fibroblasts were isolated from skin, lung, kidney and hearts of adult CD1, C57BL/6 or aSMA-RFP/COLL-EGFP mice (1) by mechanical and enzymatic tissue digestion. Briefly, tissue was chopped in small chunks that were digested using a mixture of enzymes (Miltenyi Biotec, 130- 098-305) for 1 hour at 37°C with mechanical dissociation followed by filtration through a 70 µm cell strainer and centrifugation. -
Antioxidant and Anti-Inflammatory Agents Mitigate Pathology in A
Human Molecular Genetics, 2015, Vol. 24, No. 14 3918–3928 doi: 10.1093/hmg/ddv122 Advance Access Publication Date: 9 April 2015 Original Article ORIGINAL ARTICLE Antioxidant and anti-inflammatory agents mitigate pathology in a mouse model of pseudoachondroplasia Karen L. Posey1,*, Francoise Coustry1, Alka C. Veerisetty1, Downloaded from Mohammad Hossain1, Joseph L. Alcorn1 and Jacqueline T. Hecht1,2 1Department of Pediatrics, University of Texas Medical School at Houston, Houston, TX, USA and 2Shriners Hospital for Children, Houston, TX, USA http://hmg.oxfordjournals.org/ *To whom correspondence should be addressed. Tel: +1 7135005786; Fax: +1 7135005689; Email: [email protected] Abstract Pseudoachondroplasia (PSACH), a severe short-limb dwarfing condition, results from mutations that cause misfolding of the cartilage oligomeric matrix protein (COMP). Accumulated COMP in growth plate chondrocytes activates endoplasmic reticulum stress, leading to inflammation and chondrocyte death. Using a MT-COMP mouse model of PSACH that recapitulates the molecular and clinical PSACH phenotype, we previously reported that oxidative stress and inflammation play important and at HAM-TMC Library on October 13, 2015 unappreciated roles in PSACH pathology. In this study, we assessed the ability of antioxidant and anti-inflammatory agents to affect skeletal and cellular pathology in our mouse model of PSACH. Treatment of MT-COMP mice with aspirin or resveratrol from birth to P28 decreased mutant COMP intracellular retention and chondrocyte cell death, and restored chondrocyte proliferation. Inflammatory markers associated with cartilage degradation and eosinophils were present in the joints of untreated juvenile MT-COMP mice, but were undetectable in treated mice. Most importantly, these treatments resulted in significantly increased femur length. -
S1 Table. List of Medications Analyzed in Present Study Drug
S1 Table. List of medications analyzed in present study Drug class Drugs Propofol, ketamine, etomidate, Barbiturate (1) (thiopental) Benzodiazepines (28) (midazolam, lorazepam, clonazepam, diazepam, chlordiazepoxide, oxazepam, potassium Sedatives clorazepate, bromazepam, clobazam, alprazolam, pinazepam, (32 drugs) nordazepam, fludiazepam, ethyl loflazepate, etizolam, clotiazepam, tofisopam, flurazepam, flunitrazepam, estazolam, triazolam, lormetazepam, temazepam, brotizolam, quazepam, loprazolam, zopiclone, zolpidem) Fentanyl, alfentanil, sufentanil, remifentanil, morphine, Opioid analgesics hydromorphone, nicomorphine, oxycodone, tramadol, (10 drugs) pethidine Acetaminophen, Non-steroidal anti-inflammatory drugs (36) (celecoxib, polmacoxib, etoricoxib, nimesulide, aceclofenac, acemetacin, amfenac, cinnoxicam, dexibuprofen, diclofenac, emorfazone, Non-opioid analgesics etodolac, fenoprofen, flufenamic acid, flurbiprofen, ibuprofen, (44 drugs) ketoprofen, ketorolac, lornoxicam, loxoprofen, mefenamiate, meloxicam, nabumetone, naproxen, oxaprozin, piroxicam, pranoprofen, proglumetacin, sulindac, talniflumate, tenoxicam, tiaprofenic acid, zaltoprofen, morniflumate, pelubiprofen, indomethacin), Anticonvulsants (7) (gabapentin, pregabalin, lamotrigine, levetiracetam, carbamazepine, valproic acid, lacosamide) Vecuronium, rocuronium bromide, cisatracurium, atracurium, Neuromuscular hexafluronium, pipecuronium bromide, doxacurium chloride, blocking agents fazadinium bromide, mivacurium chloride, (12 drugs) pancuronium, gallamine, succinylcholine -
In Silico Prediction of Interactions Between Site II on Human Serum Albumin and Profen Drugs
Hindawi Publishing Corporation ISRN Pharmaceutics Volume 2013, Article ID 818364, 8 pages http://dx.doi.org/10.1155/2013/818364 Research Article In Silico Prediction of Interactions between Site II on Human Serum Albumin and Profen Drugs Hideto Isogai and Noriaki Hirayama Basic Medical Science and Molecular Medicine, Tokai University School of Medicine, 143 Shimokasuya, Isehara, Kanagawa 259-1193, Japan Correspondence should be addressed to Noriaki Hirayama; [email protected] Received 21 January 2013; Accepted 6 February 2013 Academic Editors: R. A. Caceres, A. Ghosal, and H. Sah Copyright © 2013 H. Isogai and N. Hirayama. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Since binding of a drug molecule to human serum albumin (HSA) significantly affects the pharmacokinetics of the drug, it is highly desirable to predict the binding affinity of the drug. Profen drugs are a widely used class of nonsteroidal anti-inflammatory drugs and it has been reported that several members of the profen class specifically bind to one of the main binding sites named site II. The actual binding mode of only ibuprofen has been directly confirmed by X-ray crystallography. Therefore, it is of interest whether other profen drugs are site II binders. Docking simulations using multiple template structures of HSA from three crystal structures of complexes between drugs and HSA have demonstrated that most of the currently available profen drugs should be site II binders. 1. Introduction center. Based on the reliable crystal structures, structure- based approaches are possible. -
Semantic Query Modeling, Context, Section Detection, and Match Score Maximization
DutchHatTrick: Semantic query modeling, ConText, section detection, and match score maximization. Martijn Schuemie* Dolf Trieschnigg† Edgar Meij‡ ErasmusMC University of Twente University of Amsterdam [email protected] [email protected] [email protected] Introduction This report discusses the collaborative work of the ErasmusMC, University of Twente, and the University of Amsterdam on the TREC 2011 Medical track. Here, the task is to retrieve patient visits from the University of Pittsburgh NLP Repository for 35 topics. The repository consists of 101,711 patient reports, and a patient visit was recorded in one or more reports. Because the training set provided by the track organization was small and not made available until quite late in the competition, we decided to create a small training set ourselves. Not only did this allow us to test several ideas before submitting runs to TREC, it also led to several insights into the data. One finding was that synonyms are widely used. Query expansion was therefore deemed essential to achieve a reasonable performance. Query expansion has been used before in Information Retrieval (IR), and is often divided into statistical and knowledge-based query expansion. Statistical query expansion uses data derived from the corpus itself, and a well-known example is pseudo-relevance feedback [1]. In contrast, we investigated knowledge-based query expansion, which uses a knowledge base such as an ontology or a dictionary to find related terms. This type of query expansion has not always proven to be successful. For instance, Hersh et al. [2] found a decrease in overall search performance when using the Unified Medical Language System (UMLS) [3] to find related terms. -
Pharmaceutical Appendix to the Tariff Schedule 2
Harmonized Tariff Schedule of the United States (2007) (Rev. 2) Annotated for Statistical Reporting Purposes PHARMACEUTICAL APPENDIX TO THE HARMONIZED TARIFF SCHEDULE Harmonized Tariff Schedule of the United States (2007) (Rev. 2) Annotated for Statistical Reporting Purposes PHARMACEUTICAL APPENDIX TO THE TARIFF SCHEDULE 2 Table 1. This table enumerates products described by International Non-proprietary Names (INN) which shall be entered free of duty under general note 13 to the tariff schedule. The Chemical Abstracts Service (CAS) registry numbers also set forth in this table are included to assist in the identification of the products concerned. For purposes of the tariff schedule, any references to a product enumerated in this table includes such product by whatever name known. ABACAVIR 136470-78-5 ACIDUM LIDADRONICUM 63132-38-7 ABAFUNGIN 129639-79-8 ACIDUM SALCAPROZICUM 183990-46-7 ABAMECTIN 65195-55-3 ACIDUM SALCLOBUZICUM 387825-03-8 ABANOQUIL 90402-40-7 ACIFRAN 72420-38-3 ABAPERIDONUM 183849-43-6 ACIPIMOX 51037-30-0 ABARELIX 183552-38-7 ACITAZANOLAST 114607-46-4 ABATACEPTUM 332348-12-6 ACITEMATE 101197-99-3 ABCIXIMAB 143653-53-6 ACITRETIN 55079-83-9 ABECARNIL 111841-85-1 ACIVICIN 42228-92-2 ABETIMUSUM 167362-48-3 ACLANTATE 39633-62-0 ABIRATERONE 154229-19-3 ACLARUBICIN 57576-44-0 ABITESARTAN 137882-98-5 ACLATONIUM NAPADISILATE 55077-30-0 ABLUKAST 96566-25-5 ACODAZOLE 79152-85-5 ABRINEURINUM 178535-93-8 ACOLBIFENUM 182167-02-8 ABUNIDAZOLE 91017-58-2 ACONIAZIDE 13410-86-1 ACADESINE 2627-69-2 ACOTIAMIDUM 185106-16-5 ACAMPROSATE 77337-76-9