2 research outputs found
Sulforaphane protects against sodium valproate–induced acute liver injury
No full textDrug-induced hepatotoxicity is one of the most commonly encountered obstacles in the field of medical practice. Sodium valproate (VPA) is amongst many drugs with reported hepatotoxic effects. Sulforaphane (SFN) is a thiol compound of wide abundance in cruciferous plants and numerous reported therapeutic efficacies. The current investigation sheds light on the potential hepatoprotective effect of SFN against VPA-induced liver injury in rats. Twice daily I.P. VPA (700 mg/kg) for 7 days induced significant biochemical alterations and hepatic histopathological damage. SFN (0.5 mg/kg, orally) for 7 days significantly boosted liver functions biomarkers; it reduced serum ALT, AST and ALP and restored serum albumin concentration in a significant manner. Meanwhile, SFN significantly mitigated VPA-induced histopathological alterations. To highlight the mechanisms implicated in the observed hepatoprotective action, hepatic MDA and TNFÎą contents significantly declined with concomitant increase in hepatic haemoxygenase-1(HO-1) content and GSH concentration with SFN treatment. In conclusion; SFN can significantly ameliorate VPA-induced hepatotoxicity and liver injury mainly by direct association between antioxidant and anti-inflammatory properties.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author
The Effect of Pruning and Compression on Graphical Representations of the Output of a Speech Recognizer
No full textLarr vocabular y continuous speech reech ition can benefitfre an e#cient data strR turfor rrR/sentingalarE number of acoustic hypotheses compactly. Wor gr1:1 or lattices have been chosen as such an e#cientinter face between acousticroust ition engines and subsequent languageprguag ing modules. This paper firR investigates the e#ect ofprEI/-- dur ing acoustic decoding on the quality ofwor lattices and shows that by combiningdi#erEE pre ing options (at the model level and wor level), we can obtain wor lattices withcompar bleaccurE/ to theorRE/ al lattices and a manageable size. In orer to use the wor lattices as the inputfor a post-prt-RI ing language module, they shouldprx--:/1 thetar/E hypotheses andtheir scor while being as small as possible. In this paper weintr oduce awor grC comprmpR/-- algor thm that significantlyrnt ces the number ofwor-- in thegrRxEE alrRx---- entation without eliminatingutter ance hypothesesor distortRI their acousticscort . Wecompar this wor grR comprCx/)R algor thm withsever lother latticesize-rRI cing appr aches and demon strnR thereRx1C-- strx gth of the new wor gr1/ comprw sionalgor:I+ for decr: ing the number ofworC in thereR/) entation. ExperR entsar conductedacrRI corRI/ and vocabular sizes todeterE/R the consistency of theprR/--) and comprC sionrnRIIC) # 2003 Elsevier Science Ltd. AllrlRI srEIE ved. 1.I5k4 Wor latticesar often chosen as theinter/C1 between an acousticrusticRx-- and a subsequent prubsequ using amor complex language model (LM)or mor specific acoustic model because of www.elsevierw.elsevi te/csl COMPUTER SPEECH AND LANGUAGE * Corr)R)R)Rr author Tel.: +1-765-494-3652; fax: +1-765-494-3371. E-mailaddr9(--)b harRxC/1:Rwxxx/Rrx+ [email protected]/Rr (M.P.Har.RIC mike.johnson@marrx+Rwxx (M.T. Johnson),[email protected])xRwEE..
