Quantitative variables are expressed as the mean (± standard error), or median and range, and qualitative variables as absolute and relative frequencies. Comparisons between groups of quantitative and qualitative variables were made by the Wilcoxon and chi square tests, respectively. Recanalization rates were AG-014699 molecular weight assessed using Cox models. Independent predictive factors for lack of recanalization were

assessed with Cox model regression. Overall survival rates were assessed by the Kaplan-Meier method. Comparisons of recanalization rates with risk factors were made by the log rank test. All tests were two-sided, and P < 0.05 was considered significant. Data handling and analysis were performed with SPSS version 12.0 software (SPSS Inc., Chicago, IL). The study was approved by all national and, if necessary, local ethics committees. All enrolled patients agreed to participate by completing a written informed consent form after receiving complete oral and written information. One patient refused to be included in the study. Out of 138 consecutive consenting patients with noncirrhotic portal vein thrombosis, 36 were excluded for the following reasons: presentation with a portal cavernoma (n = 33), or with ruptured esophageal varices (n

= 3). Seven patients were included in the descriptive analysis, but were excluded from the therapeutic and prognostic analyses: one received low-dose Protein Tyrosine Kinase inhibitor aspirin, four patients 上海皓元医药股份有限公司 had anticoagulation introduced more than 30 days after diagnosis (at day 35, 55, 65, and 76, respectively), and two have not received anticoagulation. Therefore, 102 patients were included in the descriptive analysis and 95 patients in the therapeutic and prognostic analysis. One hundred two patients

were enrolled and followed-up for a median of 242 days (range, 0–904 days): eight in Belgium, four in Germany, 16 in Italy, 42 in France, 19 in The Netherlands, eight in Spain, and five in Switzerland. Three patients were lost to follow-up before the protocol 1-month evaluation. The main features at diagnosis are presented in Table 1. Most patients had fever or elevated C-reactive protein levels, with or without an inflammatory focus. Moderate yet clinically detectable ascites was observed in only five patients, two of whom developed intestinal infarction. However, clinically undetectable ascites was detected at imaging in 34 patients. The presence of ascites was not associated to atrophy–hypertrophy complex, jaundice, splenomegaly, time to diagnosis, or time to treatment. Splenomegaly was present in 38 (37%) patients, 15 of whom (40%) had a myeloproliferative disorder (MPD), whereas among the 64 patients without splenomegaly, only five (8%) had an MPD (P = 0.001, chi square test). Splenomegaly was not associated with atrophy–hypertrophy complex, jaundice, ascites, splenic vein thrombosis, time to diagnosis, or time to initiation of therapy.

Clinical abnormalities range from ultrasound report of fatty liver (NAFLD) to elevated transaminases (NASH), or even cirrhosis and liver cancer. BGB324 Pathogenic mechanisms include inflammatory reactions induced by cytokine and adipokine activation and oxidative stress. Antioxidant supplements, therefore, could potentially protect cellular structures against oxidative stress.

This study aims to review and analyze the potential role of Vitamin E as an anti-oxidant in patients with NASH. Methods: A systematic search for randomized controlled trials through Google Scholar, Cochrane review, GastroHep and Pubmed data, supplemented by a manual search for other relevant journals was conducted. Metaanalysis of these articles was done. Results: Randomized controlled trials (n = 424 patients) using Vitamin E in the treatment click here of NASH, the outcome being shown as decrease in the levels of liver transaminases, showed no significant effects compared to placebo. Conclusion: There was no benefit of Vitamin E therapy in the treatment of NASH based

on the primary outcome of decreased and or normalization of transaminases as the primary outcome in this meta-analysis. Key Word(s): 1. NAFLD; 2. SGPT, SGOT; 3. Vitamin E; Presenting Author: ERICKSON TENORIO, MD TENORIO Additional Authors: HIGINIO MAPPALA, MD, FPCP, FPSG, FPSDE MAPPALA Corresponding Author: ERICKSON

TENORIO, MD TENORIO Affiliations: Philippine Society of Gastroenterology Objective: Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease in adults worldwide. It is an increasingly recognized condition that may progress to end stage liver disease, cirrhosis or liver cancer. Multiple hypotheses have been postulated in its pathogenesis and several therapeutic options have been offered, ranging MCE公司 from treatment of associated metabolic conditions such as diabetes and hyperlipidemia, improving insulin resistance by weight loss, exercise and or pharmacotherapy and use of hepatoprotective agents. Bile Acids, like Ursodeoxycholic acid (UDCA) has also been shown to be effective in some studies. This study aims to evaluate the efficacy of High-dose UDCA (URSOLIV, at 30 mg/KBW) to that of standard (Std-UDCA at 15 mg/KBW). Methods: A systematic search of all randomized controlled studies thru Google, Medline, Trip base, Wiley, GastroHep and PubMed database for the National Library of Medicine, supplemented by a manual search of other relevant journals was conducted using the terms NAFLD and UDCA. There were 22 potentially related papers found. Metaanalysis was done on these papers based on our inclusion criteria.

Henry Donohue, Jr., Terrence Dore, Gregory J. Dranoff, Jonathan Duffield, Jeremy Dufour, D. Dufour, Jean-Francois Duncan, Stephen Dunn, Winston Durand, Francois Dusheiko, Geoffrey Duvoux, Christophe Ekseteen, Bertus Ekstedt, Mattias El-Youssef, Mounif Eloranta, Jyrki Engels, Eric Enns, Caroline A. Evans, Matthew Everhart, James E. Everson,

Gregory Exley, Mark Fabbrini, Elisa Faber, Klaas Nico Fabregat, Isabel Facciuto, Marcelo Factor, Valentina Apoptosis inhibitor Fallowfield, Jonathan Fan, Jian Farber, Steven Farci, Patrizia Fargion, Silvia Farrell, Geoff Feld, Jordan Feldstein, Ariel Felipo, Vicente Fellay, Jacques Feng, Sandy Feo, Francesco Feranchak, Andrew Ferenci, Peter Fernandez, Javier Nutlin 3 Fernandez, Mercedes Fernandez-Checa, Jose Fernandez-Zapico, Martin Finck, Brian Finegold, Milton Finn, Richard Flisiak, Robert Florman, Sander Fontana, Robert Forbes, Stuart Forner, Alejandro Forns, Xavier Forrest, Ewan Forton, Daniel Foster, Graham Franken, Sebastian Frayn, Keith Frazer, David Freeman, Richard

Friedman, Jacob Friedman, Joshua Friedman, Scott Fuster, Jose Gale, Michael Galle, Peter Gallicano, Ian Gane, Edward Gao, Bin Gao, Chung-fang Gao, Guangping Garcia-Pagan, Juan Carlos Garcia-Tsao, Guadalupe Gawrieh, Samer Gehring, Adam Gelman,

Irwin George, Jacob George, Sarah Gerbes, Alexander Gerken, Guido Gershwin, M. Eric Ghany, Marc Ghiazza, Paola Gholam, Pierre Giannelli, Gianluigi Gigot, Jean-Francois Gines, Pere Ginsberg, Henry N. Gish, Robert Glaser, Shannon Gluud, Lise Godoy, Patricio Goessling, Wolfram Golden-Mason, Lucy Gonzales, Emmanuel Gonzalez, Frank Goodman, Zachary Gordeuk, Victor Gordon, Fredric Grace, Norman Grakoui, Arash Gramantieri, Laura Grant, Steven Graziadei, Ivo Green, Richard Greenbaum, Linda Gressner, 上海皓元医药股份有限公司 Olav Gretch, David Grompe, Markus Grundy, Scott Guanabens, Nuria Gudbrandsen, Oddrun Guevara, Monica Guha, Indra Neil Guichelaar, Maureen Guillou, Hervé Guo, Grace Gupta, Rakesh Gupta, Sanjeev Guzman, Grace Haber, Barbara A. Hadziyannis, Stephanos Hahn, Young Halsted, Charles Han, Kwang-Hyub Han, Steven-Huy Han, Ze-Guang Harrison, Stephen Hart, John Hassan, Manal Haukeland, John Hay, David Hay, J. Eileen Hayes, Peter C. He, Ming Liang He, Ruth Heim, Markus Heimbach, Julie Helbig, Karla Heller, Theo Henderson, J.

Henry Donohue, Jr., Terrence Dore, Gregory J. Dranoff, Jonathan Duffield, Jeremy Dufour, D. Dufour, Jean-Francois Duncan, Stephen Dunn, Winston Durand, Francois Dusheiko, Geoffrey Duvoux, Christophe Ekseteen, Bertus Ekstedt, Mattias El-Youssef, Mounif Eloranta, Jyrki Engels, Eric Enns, Caroline A. Evans, Matthew Everhart, James E. Everson,

Gregory Exley, Mark Fabbrini, Elisa Faber, Klaas Nico Fabregat, Isabel Facciuto, Marcelo Factor, Valentina 3-MA Fallowfield, Jonathan Fan, Jian Farber, Steven Farci, Patrizia Fargion, Silvia Farrell, Geoff Feld, Jordan Feldstein, Ariel Felipo, Vicente Fellay, Jacques Feng, Sandy Feo, Francesco Feranchak, Andrew Ferenci, Peter Fernandez, Javier selleck screening library Fernandez, Mercedes Fernandez-Checa, Jose Fernandez-Zapico, Martin Finck, Brian Finegold, Milton Finn, Richard Flisiak, Robert Florman, Sander Fontana, Robert Forbes, Stuart Forner, Alejandro Forns, Xavier Forrest, Ewan Forton, Daniel Foster, Graham Franken, Sebastian Frayn, Keith Frazer, David Freeman, Richard

Friedman, Jacob Friedman, Joshua Friedman, Scott Fuster, Jose Gale, Michael Galle, Peter Gallicano, Ian Gane, Edward Gao, Bin Gao, Chung-fang Gao, Guangping Garcia-Pagan, Juan Carlos Garcia-Tsao, Guadalupe Gawrieh, Samer Gehring, Adam Gelman,

Irwin George, Jacob George, Sarah Gerbes, Alexander Gerken, Guido Gershwin, M. Eric Ghany, Marc Ghiazza, Paola Gholam, Pierre Giannelli, Gianluigi Gigot, Jean-Francois Gines, Pere Ginsberg, Henry N. Gish, Robert Glaser, Shannon Gluud, Lise Godoy, Patricio Goessling, Wolfram Golden-Mason, Lucy Gonzales, Emmanuel Gonzalez, Frank Goodman, Zachary Gordeuk, Victor Gordon, Fredric Grace, Norman Grakoui, Arash Gramantieri, Laura Grant, Steven Graziadei, Ivo Green, Richard Greenbaum, Linda Gressner, MCE Olav Gretch, David Grompe, Markus Grundy, Scott Guanabens, Nuria Gudbrandsen, Oddrun Guevara, Monica Guha, Indra Neil Guichelaar, Maureen Guillou, Hervé Guo, Grace Gupta, Rakesh Gupta, Sanjeev Guzman, Grace Haber, Barbara A. Hadziyannis, Stephanos Hahn, Young Halsted, Charles Han, Kwang-Hyub Han, Steven-Huy Han, Ze-Guang Harrison, Stephen Hart, John Hassan, Manal Haukeland, John Hay, David Hay, J. Eileen Hayes, Peter C. He, Ming Liang He, Ruth Heim, Markus Heimbach, Julie Helbig, Karla Heller, Theo Henderson, J.

In general, AAV8-Fah displayed a linear dose response over the range of doses administered (Fig. 4) where the highest doses administered produced the greatest gene repair. The difference in repair frequencies between the highest dose and all other doses administered was significant. In contrast, AAV2-Fah had no significant change in repair frequency over the entire range of doses administered. Overall, results indicate

that AAV8-mediated gene repair is superior to that with AAV2. The adult liver has considerably less cellular turnover than neonatal liver undergoing rapid growth and proliferation. Thus, gene repair frequencies are predicted to be lower in adults as homologous recombination is most prevalent during mitotic S-phase.37 AAV8 was chosen to LY2157299 chemical structure test the feasibility of gene repair in the nearly quiescent adult liver as it had now been demonstrated to be both faster and more efficient at gene repair than AAV2. Adult Fah5981SB mice (8-12 weeks old) were injected with 1 × 1011 vg of AAV8-Fah (n = 6), whereas age-matched littermate controls were injected with isotonic NaCl (n = 8). Mice were withdrawn from NTBC to allow selection of corrected hepatocytes. Serum for liver function tests and liver tissue were harvested >12 weeks after treatment. Mice treated with AAV8-Fah showed clinical improvement and repopulation with FAH+ hepatocytes (Fig. 5A), whereas all mice GW-572016 mouse in the control

group had

to be euthanized and showed no hepatic repopulation. Surprisingly, the initial correction frequency of FAH+ nodules was comparable to that seen with neonatal administration. The clonal expansion of corrected hepatocytes was able to reverse the tyrosinemic phenotype and was highly reproducible. Liver function tests for AST and bilirubin demonstrated near complete correction when compared to controls (Fig. 5B). Although phenotypic reversion of Fah5981SB mice indicates successful site-specific gene repair, random integration could also occur.38 To assess random integration frequencies, d3 Fah5981SB neonates were coinjected with 4 × 1010 vg of AAV8-Fah and an irrelevant serotype-matched control vector AAV8-hAAT. Post-weaning, mice were 上海皓元医药股份有限公司 subjected to NTBC withdrawal to select for corrected hepatocytes. To ensure no episomes remained, 5 × 105 random hepatocytes were then serially transplanted into eight secondary Fah5981SB recipients. After >12 weeks off NTBC, serum and liver tissue were collected at harvest. qPCR was used to determine Fah and hAAT copy numbers in each mouse (Table 1). The frequency of randomly integrated hAAT ranged from 0 (undetectable) to 0.06/dGE and averaged 0.005/dGE. Only half the hepatocytes in repopulated livers were donor-derived, thus frequencies were corrected by a factor of two, resulting in an average random integration frequency of 0.01/dGE (1%) in corrected hepatocytes.

In general, AAV8-Fah displayed a linear dose response over the range of doses administered (Fig. 4) where the highest doses administered produced the greatest gene repair. The difference in repair frequencies between the highest dose and all other doses administered was significant. In contrast, AAV2-Fah had no significant change in repair frequency over the entire range of doses administered. Overall, results indicate

that AAV8-mediated gene repair is superior to that with AAV2. The adult liver has considerably less cellular turnover than neonatal liver undergoing rapid growth and proliferation. Thus, gene repair frequencies are predicted to be lower in adults as homologous recombination is most prevalent during mitotic S-phase.37 AAV8 was chosen to Cell Cycle inhibitor test the feasibility of gene repair in the nearly quiescent adult liver as it had now been demonstrated to be both faster and more efficient at gene repair than AAV2. Adult Fah5981SB mice (8-12 weeks old) were injected with 1 × 1011 vg of AAV8-Fah (n = 6), whereas age-matched littermate controls were injected with isotonic NaCl (n = 8). Mice were withdrawn from NTBC to allow selection of corrected hepatocytes. Serum for liver function tests and liver tissue were harvested >12 weeks after treatment. Mice treated with AAV8-Fah showed clinical improvement and repopulation with FAH+ hepatocytes (Fig. 5A), whereas all mice Cabozantinib in the control

group had

to be euthanized and showed no hepatic repopulation. Surprisingly, the initial correction frequency of FAH+ nodules was comparable to that seen with neonatal administration. The clonal expansion of corrected hepatocytes was able to reverse the tyrosinemic phenotype and was highly reproducible. Liver function tests for AST and bilirubin demonstrated near complete correction when compared to controls (Fig. 5B). Although phenotypic reversion of Fah5981SB mice indicates successful site-specific gene repair, random integration could also occur.38 To assess random integration frequencies, d3 Fah5981SB neonates were coinjected with 4 × 1010 vg of AAV8-Fah and an irrelevant serotype-matched control vector AAV8-hAAT. Post-weaning, mice were 上海皓元 subjected to NTBC withdrawal to select for corrected hepatocytes. To ensure no episomes remained, 5 × 105 random hepatocytes were then serially transplanted into eight secondary Fah5981SB recipients. After >12 weeks off NTBC, serum and liver tissue were collected at harvest. qPCR was used to determine Fah and hAAT copy numbers in each mouse (Table 1). The frequency of randomly integrated hAAT ranged from 0 (undetectable) to 0.06/dGE and averaged 0.005/dGE. Only half the hepatocytes in repopulated livers were donor-derived, thus frequencies were corrected by a factor of two, resulting in an average random integration frequency of 0.01/dGE (1%) in corrected hepatocytes.

For two Group A GT1b-infected patients, no viral breakthrough occurred during 24 RG-7388 weeks of treatment and neither patient experienced

relapse during the 48-week follow-up period. For patients in Group A, trough plasma concentrations of daclatasvir 24 hours postdose on Day 14 ranged from 187-617 nM in Group A. Range in plasma concentrations of asunaprevir 12 hours postdose on Day 14 ranged from 32-501 nM. No correlation was observed between these trough plasma concentrations of daclatasvir and asunaprevir and virologic breakthrough (Table 1). In vitro resistance phenotypes (EC90 values in transient and stable replicon cell line assays) of emergent predominant resistance variants, however, were higher than observed drug exposures VX-770 in plasma for daclatasvir and asunaprevir. Review of manual pill counts and dosing diaries suggested excellent adherence to treatment except for Patient 1, who admitted to several missed asunaprevir doses within the first 2 weeks of treatment. Patient 1 (GT1a) had early viral

breakthrough with detectable drug-resistant variants as early as Week 2 (Fig. 2) and started treatment intensification with peginterferon alfa-2a and ribavirin at Week 4. Emergent NS5A-Y93N conferred 19,267-fold reduced susceptibility to daclatasvir in vitro, and persisted through posttreatment Week 48. NS3-D168Y and NS3-D168A also emerged at virologic breakthrough and conferred 93-fold and 29-fold reduced susceptibilities to asunaprevir (Table 3) with 0.23 and 0.01-fold relative replication capacities (Fig. 2), respectively, versus a GT1a (H77c) reference replicon. NS3-D168T emerged 上海皓元 as a minor variant (10%; 4/40 clones), determined by clonal analysis, at Week 12 (8 weeks into treatment intensification) conferring 205-fold reduced susceptibility to asunaprevir (Table 3) and 1.6-fold relative replication

capacity when compared to GT1a (H77c) (Fig. 2). This became the predominant variant from Week 24 (20 weeks after treatment intensification) through posttreatment Week 36. D168T may have emerged from D168A based on synonymous codon usage. The low relative replication capacity of D168A was improved by changing to D168T (see comparison of in vitro replication capacities, Fig. 2). D168T was no longer detected by clonal analysis at posttreatment Week 48 due to outgrowth of wild-type virus. It should be noted that D168G (13-fold reduced susceptibility to asunaprevir) was detected in one sequenced colony at this timepoint. The time course of HCV viral load for Patient 2 (GT1a) indicated early viral breakthrough at Week 4 followed by viral suppression during treatment intensification with peginterferon alfa-2a and ribavirin for approximately 41 weeks and viral relapse within 4 weeks of treatment discontinuation (Fig. 3).

For two Group A GT1b-infected patients, no viral breakthrough occurred during 24 BMN 673 research buy weeks of treatment and neither patient experienced

relapse during the 48-week follow-up period. For patients in Group A, trough plasma concentrations of daclatasvir 24 hours postdose on Day 14 ranged from 187-617 nM in Group A. Range in plasma concentrations of asunaprevir 12 hours postdose on Day 14 ranged from 32-501 nM. No correlation was observed between these trough plasma concentrations of daclatasvir and asunaprevir and virologic breakthrough (Table 1). In vitro resistance phenotypes (EC90 values in transient and stable replicon cell line assays) of emergent predominant resistance variants, however, were higher than observed drug exposures Idasanutlin order in plasma for daclatasvir and asunaprevir. Review of manual pill counts and dosing diaries suggested excellent adherence to treatment except for Patient 1, who admitted to several missed asunaprevir doses within the first 2 weeks of treatment. Patient 1 (GT1a) had early viral

breakthrough with detectable drug-resistant variants as early as Week 2 (Fig. 2) and started treatment intensification with peginterferon alfa-2a and ribavirin at Week 4. Emergent NS5A-Y93N conferred 19,267-fold reduced susceptibility to daclatasvir in vitro, and persisted through posttreatment Week 48. NS3-D168Y and NS3-D168A also emerged at virologic breakthrough and conferred 93-fold and 29-fold reduced susceptibilities to asunaprevir (Table 3) with 0.23 and 0.01-fold relative replication capacities (Fig. 2), respectively, versus a GT1a (H77c) reference replicon. NS3-D168T emerged 上海皓元医药股份有限公司 as a minor variant (10%; 4/40 clones), determined by clonal analysis, at Week 12 (8 weeks into treatment intensification) conferring 205-fold reduced susceptibility to asunaprevir (Table 3) and 1.6-fold relative replication

capacity when compared to GT1a (H77c) (Fig. 2). This became the predominant variant from Week 24 (20 weeks after treatment intensification) through posttreatment Week 36. D168T may have emerged from D168A based on synonymous codon usage. The low relative replication capacity of D168A was improved by changing to D168T (see comparison of in vitro replication capacities, Fig. 2). D168T was no longer detected by clonal analysis at posttreatment Week 48 due to outgrowth of wild-type virus. It should be noted that D168G (13-fold reduced susceptibility to asunaprevir) was detected in one sequenced colony at this timepoint. The time course of HCV viral load for Patient 2 (GT1a) indicated early viral breakthrough at Week 4 followed by viral suppression during treatment intensification with peginterferon alfa-2a and ribavirin for approximately 41 weeks and viral relapse within 4 weeks of treatment discontinuation (Fig. 3).

As control variable for possible geographic differences, we included the effect of ‘area’ (either Nidwalden or Zug) into the modelling. JQ1 research buy We obtained climate and landscape data from geographic information system (GIS) layers with a resolution of 100 × 100 m (Zimmermann & Kienast, 1999) from the Swiss Biological Records

Centre (CSCF, http://www.cscf.ch). We extracted climate variables and landscape features within a 100 m buffer of each watershed using zonal statistic tools in ArcGIS 9.3 (ESRI, Redlands, CA, USA). The choice of this buffer was due to the limited accessibility of the terrestrial habitat of various watersheds as well as the observation that S. salamandra strongly responds to habitat features within riparian buffers of 100–400 m (Ficetola, Padoa-Schioppa & De Bernardi, 2009). The two extracted variables ‘slope’ and ‘altitude’ are topographic characteristics of the sites (Table 1; Tanadini et al., 2012; Werner et al., in press), while the other seven variables provide information on the climate: ‘mean temperature in January’ (°C), ‘mean temperature in July’ (°C), ‘mean annual temperature’ (°C), ‘mean radiation in July’ (/100 kJ m−2), ‘mean annual radiation’ MLN8237 mw (/100 kJ m−2), ‘mean precipitation

in July’ (mm) and ‘mean annual precipitation’ (mm) (Werner et al., in press). We tested for collinearity among the

all variables using a Spearman’s medchemexpress correlation analysis. There were no strong correlations between the habitat predictors (Spearman’s correlation, all −0.5 < |r| < 0.5), suggesting that the collinearity would not strongly affect the modelling of species–habitat relationships. All seven climatic variables and the variable ‘altitude’ were significantly correlated (|r| ranging 0.7 to 0.9 or −0.7 to −0.9). Thus, we excluded the variable ‘altitude’ from all analyses. Climatic variables were processed in a principal component analysis (PCA; using varimax rotation and Kaiser normalization) to reduce the number of predictors and to create a new variable describing variation in climate among sites. We extracted the first principal component explaining 69.81% of the total variance (eigenvalue = 4.89) and used it as covariate during site-occupancy modelling. This variable (hereafter ‘PCA climate’) was correlated to the climatic predictors ‘mean annual precipitation’ (r = −0.88), ‘mean precipitation in July’ (r = −0.87), ‘mean radiation in July’ (r = −0.86), ‘mean temperature in January’ (r = 0.95), ‘mean temperature in July’ (r = 0.89) and ‘mean annual temperature’ (r = 0.86; P < 0.05 for all correlations).

As control variable for possible geographic differences, we included the effect of ‘area’ (either Nidwalden or Zug) into the modelling. see more We obtained climate and landscape data from geographic information system (GIS) layers with a resolution of 100 × 100 m (Zimmermann & Kienast, 1999) from the Swiss Biological Records

Centre (CSCF, http://www.cscf.ch). We extracted climate variables and landscape features within a 100 m buffer of each watershed using zonal statistic tools in ArcGIS 9.3 (ESRI, Redlands, CA, USA). The choice of this buffer was due to the limited accessibility of the terrestrial habitat of various watersheds as well as the observation that S. salamandra strongly responds to habitat features within riparian buffers of 100–400 m (Ficetola, Padoa-Schioppa & De Bernardi, 2009). The two extracted variables ‘slope’ and ‘altitude’ are topographic characteristics of the sites (Table 1; Tanadini et al., 2012; Werner et al., in press), while the other seven variables provide information on the climate: ‘mean temperature in January’ (°C), ‘mean temperature in July’ (°C), ‘mean annual temperature’ (°C), ‘mean radiation in July’ (/100 kJ m−2), ‘mean annual radiation’ Venetoclax (/100 kJ m−2), ‘mean precipitation

in July’ (mm) and ‘mean annual precipitation’ (mm) (Werner et al., in press). We tested for collinearity among the

all variables using a Spearman’s MCE公司 correlation analysis. There were no strong correlations between the habitat predictors (Spearman’s correlation, all −0.5 < |r| < 0.5), suggesting that the collinearity would not strongly affect the modelling of species–habitat relationships. All seven climatic variables and the variable ‘altitude’ were significantly correlated (|r| ranging 0.7 to 0.9 or −0.7 to −0.9). Thus, we excluded the variable ‘altitude’ from all analyses. Climatic variables were processed in a principal component analysis (PCA; using varimax rotation and Kaiser normalization) to reduce the number of predictors and to create a new variable describing variation in climate among sites. We extracted the first principal component explaining 69.81% of the total variance (eigenvalue = 4.89) and used it as covariate during site-occupancy modelling. This variable (hereafter ‘PCA climate’) was correlated to the climatic predictors ‘mean annual precipitation’ (r = −0.88), ‘mean precipitation in July’ (r = −0.87), ‘mean radiation in July’ (r = −0.86), ‘mean temperature in January’ (r = 0.95), ‘mean temperature in July’ (r = 0.89) and ‘mean annual temperature’ (r = 0.86; P < 0.05 for all correlations).