107 research outputs found
A Novel Inhibitor IDPP Interferes with Entry and Egress of HCV by Targeting Glycoprotein E1 in a Genotype-Specific Manner
No full textAbstractDespite recent advances in curing chronic hepatitis C (CHC), the high economic burden to therapy, viral drug resistance, difficult to treat hepatitis C virus (HCV) genotypes and patient groups are still of concern. To address this unmet medical needs, we devised strategies to identify novel viral interventions through target-free high-throughput screening of small molecules utilizing a phenotypic-based HCV infection assay. Thereby, a very potent (EC50 46 ± 26 pM) iminodipyridinopyrimidine (IDPP) drug candidate was selected, and confirmed in primary human hepatocytes (EC50 0.5 nM). IDPP mainly targets a post-attachment step of HCV without affecting endosomal acidification, prevents the secretion of infectious particles and viral cell-to-cell spread. The putative molecular target of IDPP is glycoprotein E1, as revealed by selection for viral drug resistance (Gly-257-Arg). IDPP was synergistic in combination with FDA-approved HCV drugs and inhibited pre-existing resistant HCV strains induced by today’s therapies. Interestingly, IDPP exclusively inhibited HCV genotype 2. However, we identified the genotype-specificity determining region in E1 and generated HCV genotype 1 susceptible to IDPP by changing one amino acid in E1 (Gln-257-Gly). Together, our results indicate an opportunity to provide an alternative treatment option for CHC and will shed light on the poorly understood function of HCV glycoprotein E1.</jats:p
The FDA-approved drug irbesartan inhibits HBV-infection in HepG2 cells stably expressing sodium taurocholate co-transporting polypeptide
No full textBACKGROUND: Little is known about the early steps of the HBV life cycle due to the lack of susceptible cells permissive for viral infection. Hence, viral entry has not been exploited for antiviral targets, but the recent seminal discovery of sodium taurocholate co-transporting polypeptide (NTCP) as the cellular receptor for HBV entry opened up many avenues of investigation, making HBV entry amenable to therapeutic intervention.
METHODS: In order to exploit HBV entry, we established a HepG2-NTCP cell line that supports HBV infection. Over 70% of cells were infected at a dose of 10(4) genome equivalents (GEq) per cell. Several FDA-approved drugs with NTCP-inhibiting activity were tested for their ability to inhibit HBV infection of the cell line.
RESULTS: Consistent with their NTCP inhibitory activities, our results showed that several of them inhibit HBV infection. In particular, irbesartan, a drug used for the treatment of hypertension, inhibits HBV infection at the 50% effective concentration value of 35 μM.
CONCLUSIONS: The observation that the pharmacological inhibitors of the NTCP transporter could block HBV entry suggests that NTCP represents an attractive molecular target for therapeutic intervention in HBV infection.ope
Evolutionary functional black-box testing in an industrial setting
No full textDuring the past years, evolutionary testing research has reported encouraging results for automated functional (i.e. black-box) testing. However, despite promising results, these techniques have hardly been applied to complex, real-world systems and as such, little is known about their scalability, applicability, and acceptability in industry. In this paper, we describe the empirical setup used to study the use of evolutionary functional testing in industry through two case studies, drawn from serial production development environments at Daimler and Berner & Mattner Systemtechnik, respectively. Results of the case studies are presented, and research questions are assessed based on them. In summary, the results indicate that evolutionary functional testing in an industrial setting is both scalable and applicable. However, the creation of fitness functions is time-consuming. Although in some cases, this is compensated by the results, it is still a significant factor preventing functional evolutionary testing from more widespread use in industry.This work is supported by EU grant IST-33472 (EvoTest). For their support and help, we would like to thank Mark Harman, Kiran Lakhotia and Youssef Hassoun from Kings College London; Marc Schoenauer and Luis da Costa from INRIA; Jochen Hansel from Fraunhofer FIRST; Dimitar Dimitrov and Ivaylo Spasov from RILA; and Dimitris Togias from European Dynamics.Vos ., TE.; Lindlar, FF.; Wilmes, B.; Windisch, A.; Baars, AI.; Kruse, PM.; Gross, H.... (2013). Evolutionary functional black-box testing in an industrial setting. Software Quality Journal. 21(2):259-288. doi:10.1007/s11219-012-9174-yS259288212Description of evolution engine parameters. http://guide.gforge.inria.fr/eeparams/EEngineParameters.pdf . Last accessed April 19, 2011.ETF user manual and cookbook. http://evotest.iti.upv.es . Last accessed April 13, 2011.GUIDE. http://gforge.inria.fr/projects/guide/ . Last accessed April 13, 2011.Evotest. http://evotest.iti.upv.es (2006). Last accessed April 13, 2011.Arcuri, A., White, D. R., Clark, J., & Yao, X. (2008). Multi-objective improvement of software using co-evolution and smart seeding. In: X. Li, M. Kirley, M. Zhang, D. G. Green, V. Ciesielski, H. A. Abbass, Z. Michalewicz, T. Hendtlass, K. Deb, K. C. Tan, J. Branke, & Y. Shi (Eds.), Proceedings of the 7th international conference on simulated evolution and learning (SEAL ’08), LNCS (Vol. 5361, pp. 61–70). Melbourne, Australia: Springer.Baresel, A., Pohlheim, H., & Sadeghipour, S. (2003). Structural and functional sequence test of dynamic and state-based software with evolutionary algorithms. In GECCO (pp. 2428–2441).Beizer B. (1990). Software testing techniques. London: International Thomson Computer Press.Briand L. C. (2007). A critical analysis of empirical research in software testing. In: Empirical software engineering and measurement, 2007. First International Symposium on ESEM 2007 (pp. 1–8).Bühler, O., & Wegener, J. (2004). Automatic testing of an autonomous parking system using evolutionary computation. In Proceedings of SAE 2004 world congress (pp. 115–122).Bühler, O., & Wegener, J. (2008). Evolutionary functional testing. Computers & Operations Research, 35(10), 3144–3160.Chan, B., Denzinger, J., Gates, D., Loose, K., & Buchanan, J. (2004). Evolutionary behaviour testing of commercial computer games. In Proceedings of CEC 2004, Portland (pp. 125–132).DaCosta, L., Fialho, A., Schoenauer, M., & Sebag, M. (2008). Adaptive operator selection with dynamic multi-armed bandits. In Proceedings of the 10th annual conference on genetic and evolutionary computation, GECCO ’08 (pp. 913–920). New York, NY: ACM. DOI http://doi.acm.org/10.1145/1389095.1389272 . http://doi.acm.org/10.1145/1389095.1389272 .Fewster, M., & Graham, D. (1999). Software test automation: effective use of test execution tools. New York, NY: ACM Press/Addison-Wesley Publishing Co.Goldberg, D.~E. (1989). Genetic algorithms in search, optimization and machine learning. Boston: Addison Wesley.Grochtmann, M., & Wegener, J. (1998). Evolutionary testing of temporal correctness. In: Proceedings of the 2nd international software quality week Europe (QWE 1998). Brussels, Belgium.Gros, H. G. (2003). Evaluation of dynamic, optimisation-based worst-case execution time analysis. In: Proceedings of the international conference on information technology: Prospects and challenges in the 21st century, (Vol. 1, pp. 8–14).Gross, H., Kruse, P. M., Wegener, J., Vos, T. (2009). Evolutionary white-box software test with the evotest framework: A progress report. In ICSTW ’09: Proceedings of the IEEE international conference on software testing, verification, and validation workshops (pp. 111–120). IEEE Computer Society, Washington, DC, USA.Harman, M., Hu, L., Hierons, R., Baresel, A., & Sthamer, H. (2002). Improving evolutionary testing by flag removal. In Proceedings of the genetic and evolutionary computation conference (GECCO 2002) (pp. 1233 – 1240). Morgan Kaufmann, New York, USA.Holland, J.H. (1975). Adaptation in natural and artificial systems. Ann Arbor: University of Michigan Press.Jones, B., Sthamer, H., & Eyres, D. (1996). Automatic structural testing using genetic algorithms. The Software Engineering Journal, 11(5), 299–306.Juristo, N., Moreno, A., & Vegas, S. (2004). Reviewing 25 years of testing technique experiments. Journal of Empirical Software Engineering 9(1), 7–44.Keijzer, M., Merelo, J. J., Romero, G., & Schoenauer, M. (2001). Evolving objects: A general purpose evolutionary computation library. In Artificial evolution (pp. 231–244). http://citeseer.ist.psu.edu/keijzer01evolving.html .Kitchenham, B. A., Pfleeger, S. L., Pickard, L. M., Jones, P. W., Hoaglin, D. C., Emam, K. E., et al. (2002). Preliminary guidelines for empirical research in software engineering. IEEE Transactions on Software Engineering, 28(8), 721–734.Klimke, A. (2003) How to access Matlab from Java, IANS report 2003/005. Tech. rep., University of Stuttgart. http://preprints.ians.uni-stuttgart.de .Kruse, P. M., Wegener, J., & Wappler, S. (2009). A highly configurable test system for evolutionary black-box testing of embedded systems. In GECCO ’09: Proceedings of the 11th annual conference on genetic and evolutionary computation (pp. 1545–1552). New York, NY: ACM. http://doi.acm.org/10.1145/1569901.1570108 .Lethbridge, T. C., Sim, S. E., & Singer, J. (2005). Studying software engineers: Data collection techniques for software field studies. Empirical Software Engineering, 10(3), 311–341.Lindlar, F., Windisch, A., & Wegener, J. (2010). Integrating model-based testing with evolutionary functional testing. In Proceedings of the 3rd international conference on software testing, verification, and validation workshops (ICSTW 2010) (pp. 163–172). Washington, DC: IEEE Computer Society.McMinn, P. (2004). Search-based software test data generation: A survey. Software Testing, Verification and Reliability, 14(2), 105–156.McMinn, P. (2011). Search-based software testing: Past, present and future. In Proceedings of the 4th international workshop on search-based software testing (SBST 2011).Messina. http://www.berner-mattner.com/en/automotive-messina.php . Last accessed Feb 3, 2010.Mueller, F., & Wegener, J. (1998). A comparison of static analysis and evolutionary testing for the verification of timing constraints. In RTAS ’98: Proceedings of the 4th IEEE real-time technology and applications symposium (p. 144). Washington, DC: IEEE Computer Society.Pargas, R. P., Harrold, M. J., & Peck, R. R. (1999). Test-data generation using genetic algorithms. Journal of Software Testing, Verification and Reliability, 9(4), 263–282.Perry, D. E., Porter, A. A., & Votta, L. G. (2000). Empirical studies of software engineering: A roadmap. In: ICSE ’00: Proceedings of the conference on the future of software engineering, (pp. 345–355). ACM.Perry, D. E., Sim, S. E., & Easterbrook, S. (2005). Case studies for software engineers. In SEW ’05: Proceedings of the 29th annual IEEE/NASA software engineering workshop—Tutorial notes (pp. 96–159). Washington, DC: IEEE Computer Society.Pohlheim, H. (2000). Evolutionäre algorithmen: Verfahren, operatoren und hinweise für die Praxis. Springer, Berlin: Heidelberg [u.a.].Sthamer, H., & Wegener, J. (2002). Using evolutionary testing to improve efficiency and quality in software testing. In Proceedings of 2nd Asia-Pacific conference on software testing.Tlili, M., Sthamer, H., Wappler, S., & Wegener, J. (2006). Improving evolutionary real-time testing by seeding structural test data. In Proceedings of the congress on evolutionary computation (CEC) (pp. 3227–3233). IEEE.Tlili, M., Wappler, S., Sthamer, H., & Wegener, J. (2006). Improving evolutionary real-time testing. In Proceedings of the 8th annual conference on genetic and evolutionary computation (GECCO) (pp. 1917–1924). New York: ACM Press.Tracey, N., Clark, J., Mander, K., & McDermid, J. (2000). Automated test-data generation for exception conditions. Software: Practice and Experience, 30(1), 61–79.Vos, T., Baars, A., Lindlar, F., Kruse, P., Windisch, A., & Wegener, J. (2010). Industrial scaled automated structural testing with the evolutionary testing tool. In Proceedings of the 3rd international conference on software testing, verification and validation (ICST2010), Paris (France) (pp. 175–184). IEEE Computer Society.Wegener, J., Buhr, K., & Pohlheim, H. (2002). Automatic test data generation for structural testing of embedded software systems by evolutionary testing. In GECCO ’02: Proceedings of the genetic and evolutionary computation conference (pp. 1233–1240). San Francisco, CA: Morgan Kaufmann Publishers Inc.Wegener, J., Grimm, K., Grochtmann, M., Sthamer, H., & Jones, B. (1996). Systematic testing of real-time systems. In Proceedings of the 4th European international conference on software testing, analysis and review. Amsterdam, The Netherlands.Windisch, A., & Al Moubayed, N. (2009). Signal generation for search-based testing of continuous systems. In Proceedings of the 2nd international conference on software testing, verification, and validation workshops (pp. 121–130). Washington, DC: IEEE Computer Society.Windisch, A., Lindlar, F., Topuz, S., & Wappler, S. (2009). Evolutionary functional testing of continuous control systems. In GECCO ’09: Proceedings of the 11th annual conference on genetic and evolutionary computation (pp. 1943–1944). New York, NY: ACM.Windisch, A., Lindlar, F., Topuz, S., & Wappler, S. (2009). Evolutionary functional testing of continuous control systems. In Proceedings of the 11th annual conference on genetic and evolutionary computation (GECCO) (pp. 1943–1944). New York, NY: ACM
Virtual Screening in Hepatitis B Virus Drug Discovery: Current Stateof- the-Art and Future Perspectives
No full textInternational audienceHepatitis B Virus (HBV) is a major global health burden. Interferon alpha and nucleos(t)ide analogues are currently the standard-of-care for chronic HBV infection. However, these antiviral agents have limited efficacy and do not result in a sustained virological response in the majority of infected patients. Virtual Screening (VS) strategies have now a strong impact on drug discovery, the strength of this research field has been corroborated by recent contributions in the development of novel drug candidates which are in clinical trials or which are already available in the clinics. In this context, different VS strategies have been applied to HBV in order to discover novel inhibitors. In this review, we summarize the VS efforts to identify and design novel HBV interventions. We believe that the combination of in silico and in vitro tools can lead to faster validation of novel drug targets which could accelerate the HBV drug discovery and development efforts
Neuronal inclusion protein TDP-43 has no primary genetic role in FTD and ALS
No full textThe nuclear TAR DNA binding protein (TDP-43) is deposited in ubiquitin-positive inclusions in frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS), two clinicopathologically overlapping neurodegenerative diseases. In this study we excluded simple and dosage mutations in the gene encoding TDP-43 (TARDBP) from an extended series of FTD, FTD-ALS and ALS patients. Further, we did not identify association of common genetic variants in these patients. Our data implicate that TDP-43 has no primary genetic role in the pathophysiological mechanisms underlying CNS neurodegeneration in these diseases
Impact of Pseudomonas aeruginosa infection on respiratory muscle function in adult cystic fibrosis patients
No full textBackground:Pseudomonas aeruginosa infection impairs respiratory muscle function in adolescents with cystic fibrosis, but its impact on adult patients has not been characterised. Objectives: To investigate respiratory muscle function in adult cystic fibrosis patients according to P. aeruginosa status (repetitive samples over 12 months). Methods: The pressure-time index of the respiratory muscles (PTImus), a measure of their efficiency, served as the primary outcome. In addition, respiratory load and maximal respiratory muscle strength were assessed. Results: In 51 patients examined (65% female; median age 32 years, IQR 24-40), a median of 3.0 (IQR 2-4) different pathogens was found in each patient. The PTImus was 0.113 and 0.126 in Pseudomonas-positive (n = 33) and -negative (n = 18) patients, respectively (p = 0.53). Univariate analysis showed a lower PTImus in male than in female patients (p = 0.006). Respiratory muscle load and strength were otherwise comparable, with the exception of higher nasal sniff pressures in Pseudomonas-positive patients who were chronically infected (>50% of positive samples). Quality of Life (according to the Cystic Fibrosis Questionnaire-Revised) was higher if both respiratory load and the PTImus were low (high respiratory muscle efficiency). Conclusions: Chronic P. aeruginosa infection does not influence respiratory muscle efficiency in adult cystic fibrosis patients with otherwise multiple co-infections. In addition, patients with reduced respiratory muscle efficiency had worse Quality of Life
Alternative approaches for efficient inhibition of hepatitis C virus RNA replication by small interfering RNAs.
No full textPersistent infection with hepatitis C virus (HCV) is a leading cause of chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma. It has recently been shown that HCV RNA replication is susceptible to small interfering RNAs (siRNAs), but the antiviral activity of siRNAs depends very much on their complementarity to the target sequence. Thus, the high degree of sequence diversity between different HCV genotypes and the rapid evolution of new quasispecies is a major problem in the development of siRNA-based gene therapies. For this study, we developed two alternative strategies to overcome these obstacles. In one approach, we used endoribonuclease-prepared siRNAs (esiRNAs) to simultaneously target multiple sites of the viral genome. We show that esiRNAs directed against various regions of the HCV coding sequence as well as the 5' nontranslated region (5' NTR) efficiently block the replication of subgenomic and genomic HCV replicons. In an alternative approach, we generated pseudotyped retroviruses encoding short hairpin RNAs (shRNAs). A total of 12 shRNAs, most of them targeting highly conserved sequence motifs within the 5' NTR or the early core coding region, were analyzed for their antiviral activities. After the transduction of Huh-7 cells containing a subgenomic HCV replicon, we found that all shRNAs targeting sequences in domain IV or nearby coding sequences blocked viral replication. In contrast, only one of seven shRNAs targeting sequences in domain II or III had a similar degree of antiviral activity, indicating that large sections of the NTRs are resistant to RNA interference. Moreover, we show that naive Huh-7 cells that stably expressed certain 5' NTR-specific shRNAs were largely resistant to a challenge with HCV replicons. These results demonstrate that the retroviral transduction of HCV-specific shRNAs provides a new possibility for antiviral intervention
Effects of a Comprehensive Pulmonary Rehabilitation in Severe Post-COVID-19 Patients
No full textBACKGROUND
Severe COVID-19 infection often leads to impairments requiring pulmonary rehabilitation (PR) following the acute phase. Little is known about the efficacy of PR in these patients. We therefore compared post-COVID-19 patients (PG) referred to PR patients with other lung diseases (LG).
METHODS
99 PG were admitted to PR. In a prospective design, the results of PG were collected and compared to the results of LG of 2019 (n = 419) according to Functional Independence Measurement (FIM), Cumulative Illness Rating Scale (CIRS), 6-min walk test (6-MWT), duration of PR, and Feeling Thermometer (FT).
RESULTS
According to age, sex, and CIRS, both groups showed no significant differences. The improvements in the 6-MWT in the pre to post comparison were on average 180 (±101) meters for PG and 102 (±89) meters for LG (p < 0.001). FT showed a significant enhancement for PG of 21 (±14) points and for LG of 17 (±16) points (p < 0.039), while FIM significantly increased by 11 (±10) points in PG and 7 (±8) points in LG (p < 0.001).
CONCLUSIONS
Comprehensive PR in PG is very effective according to the results in FIM, 6-MWT and FT. Therefore, we recommend PR following severe post-COVID-19 infections
Abl Tyrosine Kinase Regulates Hepatitis C Virus Entry
No full textAbl is a central regulator of multiple cellular processes controlling actin dynamics, proliferation, and differentiation. Here, we showed that knockdown of Abl impaired hepatitis C virus (HCV) propagation. Treatment of Abl tyrosine kinase-specific inhibitor, imatinib and dasatinib, also significantly decreased HCV RNA and protein levels in HCV-infected cells. We showed that both imatinib and dasatinib selectively inhibited HCV infection at the entry step of HCV life cycle, suggesting that Abl kinase activity may be necessary for HCV entry. Using HCV pseudoparticle infection assays, we verified that Abl is required for viral entry. By employing transferrin uptake and immunofluorescence assays, we further demonstrated that Abl was involved in HCV entry at a clathrin-mediated endocytosis step. These data suggest that Abl may represent a novel host factor for HCV entry.ope
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