Efecto del extracto de metanol de Achyranthes aspera linn. sobre la hepatotoxicidad inducida por rifampicina en ratas

Methanol extract of aerial parts of Achyranthes aspera Linn. (Family: Amaranthaceae) was tested for its effect onrifampicin-induced hepatotoxicity in albino rats at five dose levels. Rifampicin intoxication in rats significantly (p < 0.001)elevated the levels of SGPT, SGOT, ALKP, and total bilirubin, which indicated acute hepatocellular, damage and biliaryobstruction. Methanol extract showed dose dependent decrease in the levels of SGPT, SGOT, ALKP and total bilirubin.Minimum effective dose of extract was found to be 100 mg/kg body weight. Results obtained from histopathological studiesalso supported hepatoprotective activity of drug against rifampicin induced hepatotoxicity. Thus study demonstrates thatA. aspera possess anti-hepatotoxic effect against rifampicin.Se analizó el extracto de metanol de las partes aéreas de Achyranthes aspera Linn. (Familia: Amaranthaceae) paracomprobar su efecto sobre la hepatotoxicidad inducida por rifampicina en ratas albinas en cinco niveles de dosis.La intoxicación por rifampicina en ratas elevó de forma significativa (p > 0,001) los niveles de SGPT-ALT, SGOTAST,FA y bilirrubina total, hecho que fue indicativo de obstrucción biliar y daño hepatocelular agudo. El extractode metanol mostró un descenso dosis-dependiente de los niveles de SGPT-ALT, SGOT-AST, FA y bilirrubina total.La dosis mínima eficaz de extracto fue 100 mg/kg de peso corporal. Los resultados obtenidos de los estudioshistopatológicos también confirmaron la actividad hepatoprotectora del fármaco frente a la hepatotoxicidad inducidapor rifampicina. Por tanto, el estudio demostró que A. aspera posee un efecto antihepatotóxico frente a la rifampicina

Gabapentin for the hemodynamic response to intubation: systematic review and meta-analysis

Purpose Endotracheal intubation is the gold standard for securing the airway before surgery. Nevertheless, this procedure can produce an activation of the sympathetic nervous system and result in a hemodynamic response which, in high-risk patients, may lead to cardiovascular instability and myocardial ischemia. The aim of this review was to evaluate whether gabapentin can attenuate this response and whether such an attenuation could translate into reduced myocardial ischemia and mortality. Source We searched MEDLINE®, EMBASE™, CINAHL, AMED, and unpublished clinical trial databases for randomized-controlled trials that compared gabapentin with control, fentanyl, clonidine, or beta blockers for attenuating the hemodynamic response to intubation. Primary outcomes were mortality, myocardial infarction, and myocardial ischemia. Secondary outcomes were hemodynamic changes following intubation. Principal findings We included 29 randomized trials with only two studies at low risk of bias. No data were provided for the primary outcomes and no studies included high-risk patients. The use of gabapentin resulted in attenuation in the rise in mean arterial blood pressure [mean difference (MD), −12 mmHg; 95% confidence interval (CI), −17 to −8] and heart rate (MD, −8 beats·min−1; 95% CI, −11 to −5) one minute after intubation. Gabapentin also reduced the risk of hypertension or tachycardia requiring treatment (risk ratio, 0.15; 95% CI, 0.05 to 0.48). Data were limited on adverse hemodynamic events such as bradycardia and hypotension. Conclusion It remains unknown whether gabapentin improves clinically relevant outcomes such as death and myocardial infarction since studies failed to report on these. Nevertheless, gabapentin attenuated increases in heart rate and blood pressure following intubation when compared with the control group. Even so, the studies included in this review were at potential risk of bias. Moreover, they did not include high-risk patients or report adverse hemodynamic outcomes. Future studies are required to address these limitations

A global reference for human genetic variation

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.We thank the many people who were generous with contributing their samples to the project: the African Caribbean in Barbados; Bengali in Bangladesh; British in England and Scotland; Chinese Dai in Xishuangbanna, China; Colombians in Medellin, Colombia; Esan in Nigeria; Finnish in Finland; Gambian in Western Division – Mandinka; Gujarati Indians in Houston, Texas, USA; Han Chinese in Beijing, China; Iberian populations in Spain; Indian Telugu in the UK; Japanese in Tokyo, Japan; Kinh in Ho Chi Minh City, Vietnam; Luhya in Webuye, Kenya; Mende in Sierra Leone; people with African ancestry in the southwest USA; people with Mexican ancestry in Los Angeles, California, USA; Peruvians in Lima, Peru; Puerto Ricans in Puerto Rico; Punjabi in Lahore, Pakistan; southern Han Chinese; Sri Lankan Tamil in the UK; Toscani in Italia; Utah residents (CEPH) with northern and western European ancestry; and Yoruba in Ibadan, Nigeria. Many thanks to the people who contributed to this project: P. Maul, T. Maul, and C. Foster; Z. Chong, X. Fan, W. Zhou, and T. Chen; N. Sengamalay, S. Ott, L. Sadzewicz, J. Liu, and L. Tallon; L. Merson; O. Folarin, D. Asogun, O. Ikpwonmosa, E. Philomena, G. Akpede, S. Okhobgenin, and O. Omoniwa; the staff of the Institute of Lassa Fever Research and Control (ILFRC), Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria; A. Schlattl and T. Zichner; S. Lewis, E. Appelbaum, and L. Fulton; A. Yurovsky and I. Padioleau; N. Kaelin and F. Laplace; E. Drury and H. Arbery; A. Naranjo, M. Victoria Parra, and C. Duque; S. Däkel, B. Lenz, and S. Schrinner; S. Bumpstead; and C. Fletcher-Hoppe. Funding for this work was from the Wellcome Trust Core Award 090532/Z/09/Z and Senior Investigator Award 095552/Z/11/Z (P.D.), and grants WT098051 (R.D.), WT095908 and WT109497 (P.F.), WT086084/Z/08/Z and WT100956/Z/13/Z (G.M.), WT097307 (W.K.), WT0855322/Z/08/Z (R.L.), WT090770/Z/09/Z (D.K.), the Wellcome Trust Major Overseas program in Vietnam grant 089276/Z.09/Z (S.D.), the Medical Research Council UK grant G0801823 (J.L.M.), the UK Biotechnology and Biological Sciences Research Council grants BB/I02593X/1 (G.M.) and BB/I021213/1 (A.R.L.), the British Heart Foundation (C.A.A.), the Monument Trust (J.H.), the European Molecular Biology Laboratory (P.F.), the European Research Council grant 617306 (J.L.M.), the Chinese 863 Program 2012AA02A201, the National Basic Research program of China 973 program no. 2011CB809201, 2011CB809202 and 2011CB809203, Natural Science Foundation of China 31161130357, the Shenzhen Municipal Government of China grant ZYC201105170397A (J.W.), the Canadian Institutes of Health Research Operating grant 136855 and Canada Research Chair (S.G.), Banting Postdoctoral Fellowship from the Canadian Institutes of Health Research (M.K.D.), a Le Fonds de Recherche duQuébec-Santé (FRQS) research fellowship (A.H.), Genome Quebec (P.A.), the Ontario Ministry of Research and Innovation – Ontario Institute for Cancer Research Investigator Award (P.A., J.S.), the Quebec Ministry of Economic Development, Innovation, and Exports grant PSR-SIIRI-195 (P.A.), the German Federal Ministry of Education and Research (BMBF) grants 0315428A and 01GS08201 (R.H.), the Max Planck Society (H.L., G.M., R.S.), BMBF-EPITREAT grant 0316190A (R.H., M.L.), the German Research Foundation (Deutsche Forschungsgemeinschaft) Emmy Noether Grant KO4037/1-1 (J.O.K.), the Beatriu de Pinos Program grants 2006 BP-A 10144 and 2009 BP-B 00274 (M.V.), the Spanish National Institute for Health Research grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER (A.O.), Ewha Womans University (C.L.), the Japan Society for the Promotion of Science Fellowship number PE13075 (N.P.), the Louis Jeantet Foundation (E.T.D.), the Marie Curie Actions Career Integration grant 303772 (C.A.), the Swiss National Science Foundation 31003A_130342 and NCCR “Frontiers in Genetics” (E.T.D.), the University of Geneva (E.T.D., T.L., G.M.), the US National Institutes of Health National Center for Biotechnology Information (S.S.) and grants U54HG3067 (E.S.L.), U54HG3273 and U01HG5211 (R.A.G.), U54HG3079 (R.K.W., E.R.M.), R01HG2898 (S.E.D.), R01HG2385 (E.E.E.), RC2HG5552 and U01HG6513 (G.T.M., G.R.A.), U01HG5214 (A.C.), U01HG5715 (C.D.B.), U01HG5718 (M.G.), U01HG5728 (Y.X.F.), U41HG7635 (R.K.W., E.E.E., P.H.S.), U41HG7497 (C.L., M.A.B., K.C., L.D., E.E.E., M.G., J.O.K., G.T.M., S.A.M., R.E.M., J.L.S., K.Y.), R01HG4960 and R01HG5701 (B.L.B.), R01HG5214 (G.A.), R01HG6855 (S.M.), R01HG7068 (R.E.M.), R01HG7644 (R.D.H.), DP2OD6514 (P.S.), DP5OD9154 (J.K.), R01CA166661 (S.E.D.), R01CA172652 (K.C.), P01GM99568 (S.R.B.), R01GM59290 (L.B.J., M.A.B.), R01GM104390 (L.B.J., M.Y.Y.), T32GM7790 (C.D.B., A.R.M.), P01GM99568 (S.R.B.), R01HL87699 and R01HL104608 (K.C.B.), T32HL94284 (J.L.R.F.), and contracts HHSN268201100040C (A.M.R.) and HHSN272201000025C (P.S.), Harvard Medical School Eleanor and Miles Shore Fellowship (K.L.), Lundbeck Foundation Grant R170-2014-1039 (K.L.), NIJ Grant 2014-DN-BX-K089 (Y.E.), the Mary Beryl Patch Turnbull Scholar Program (K.C.B.), NSF Graduate Research Fellowship DGE-1147470 (G.D.P.), the Simons Foundation SFARI award SF51 (M.W.), and a Sloan Foundation Fellowship (R.D.H.). E.E.E. is an investigator of the Howard Hughes Medical Institute

A 3.5-Approximation Algorithm for Sorting by Intergenic Transpositions

International audienceGenome Rearrangements affect large stretches of genomes during evolution. One of the most studied genome rearrangement is the transposition, which occurs when a sequence of genes is moved to another position inside the genome. Mathematical models have been used to estimate the evolutionary distance between two different genomes based on genome rearrangements. However, many of these models have focused only on the (order of the) genes of a genome, disregarding other important elements in it. Recently, researchers have shown that considering existing regions between each pair of genes, called intergenic regions, can enhance the distance estimation in realistic data. In this work, we study the transposition distance between two genomes, but we also consider intergenic regions, a problem we name Sorting Permutations by Intergenic Transpositions (SbIT). We show that this problem is NP-hard and propose a 3.5-approximation algorithm for it