Inducible arginase 1 deficiency in mice leads to hyperargininemia and altered amino acid metabolism

Arginase deficiency is a rare autosomal recessive disorder resulting from a loss of the liver arginase isoform, arginase 1 (ARG1), which is the final step in the urea cycle for detoxifying ammonia. ARG1 deficiency leads to hyperargininemia, characterized by progressive neurological impairment, persistent growth retardation and infrequent episodes of hyperammonemia. Using the Cre/loxP-directed conditional gene knockout system, we generated an inducible Arg1-deficient mouse model by crossing "floxed" Arg1 mice with CreER(T2) mice. The resulting mice (Arg-Cre) die about two weeks after tamoxifen administration regardless of the starting age of inducing the knockout. These treated mice were nearly devoid of Arg1 mRNA, protein and liver arginase activity, and exhibited symptoms of hyperammonemia. Plasma amino acid analysis revealed pronounced hyperargininemia and significant alterations in amino acid and guanidino compound metabolism, including increased citrulline and guanidinoacetic acid. Despite no alteration in ornithine levels, concentrations of other amino acids such as proline and the branched-chain amino acids were reduced. In summary, we have generated and characterized an inducible Arg1-deficient mouse model exhibiting several pathologic manifestations of hyperargininemia. This model should prove useful for exploring potential treatment options of ARG1 deficiency

Efficient single-step rapeseed oleosome extraction using twin-screw press

Oil in seeds is encapsulated in oleosomes, which are small lipid droplets surrounded by a phospholipid-protein monolayer. The currently proposed method to extract intact oleosomes includes mixing seeds with alkaline media in a ratio 1:7, batch blending and filtering. In this work, we propose the use of a twin-screw press to perform the oleosome extraction at pH 7. The results show that similarly to blender extraction, twin-screw press recovers ⁓60% of the oleosomes; however the twin-screw press is able to achieve this yield even when just pure water is used. While in the blender extraction, the yield depends on ionic strength and pH of the extraction media, when using twin-screw press, the oleosome extraction yield predominantly depends on the mechanical forces. These shear forces are able to break the cell walls and release the cellular material while maintaining the integrity of oleosomes. The oleosomes extracted with twin-screw press have similar characteristics than those obtained by the blending process. Overall, twin-screw press seems a promising alternative to scale-up the oleosome aqueous extraction, especially as neutral pH can be used and the water usage is significantly reduced. Additionally, preliminary results showed that the yield can increase up to 90 wt%.</p

Strategies to rescue the consequences of inducible arginase-1 deficiency in mice

Arginase-1 catalyzes the conversion of arginine to ornithine and urea, which is the final step of the urea cycle used to remove excess ammonia from the body. Arginase-1 deficiency leads to hyperargininemia in mice and man with severe lethal consequences in the former and progressive neurological impairment to varying degrees in the latter. In a tamoxifen-induced arginase-1 deficient mouse model, mice succumb to the enzyme deficiency within 2 weeks after inducing the knockout and retain <2 % enzyme in the liver. Standard clinical care regimens for arginase-1 deficiency (low-protein diet, the nitrogen-scavenging drug sodium phenylbutyrate, ornithine supplementation) either failed to extend lifespan (ornithine) or only minimally prolonged lifespan (maximum 8 days with low-protein diet and drug). A conditional, tamoxifen-inducible arginase-1 transgenic mouse strain expressing the enzyme from the Rosa26 locus modestly extended lifespan of neonatal mice, but not that of 4-week old mice, when crossed to the inducible arginase-1 knockout mouse strain. Delivery of an arginase-1/enhanced green fluorescent fusion construct by adeno-associated viral delivery (rh10 serotype with a strong cytomegalovirus-chicken beta-actin hybrid promoter) rescued about 30% of male mice with lifespan prolongation to at least 6 months, extensive hepatic expression and restoration of significant enzyme activity in liver. In contrast, a vector of the AAV8 serotype driven by the thyroxine-binding globulin promoter led to weaker liver expression and did not rescue arginase-1 deficient mice to any great extent. Since the induced arginase-1 deficient mouse model displays a much more severe phenotype when compared to human arginase-1 deficiency, these studies reveal that it may be feasible with gene therapy strategies to correct the various manifestations of the disorder and they provide optimism for future clinical studies

Silhouette + Attraction: A Simple and Effective Method for Text Clustering

[EN] This article presents silhouette attraction (Sil Att), a simple and effective method for text clustering, which is based on two main concepts: the silhouette coefficient and the idea of attraction. The combination of both principles allows us to obtain a general technique that can be used either as a boosting method, which improves results of other clustering algorithms, or as an independent clustering algorithm. The experimental work shows that Sil Att is able to obtain high-quality results on text corpora with very different characteristics. Furthermore, its stable performance on all the considered corpora is indicative that it is a very robust method. This is a very interesting positive aspect of Sil Att with respect to the other algorithms used in the experiments, whose performances heavily depend on specific characteristics of the corpora being considered.This research work has been partially funded by UNSL, CONICET (Argentina), DIANA-APPLICATIONS-Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) research project, and the WIQ-EI IRSES project (grant no. 269180) within the FP 7 Marie Curie People Framework on Web Information Quality Evaluation Initiative. The work of the third author was done also in the framework of the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems.Errecalde, M.; Cagnina, L.; Rosso, P. (2015). Silhouette + Attraction: A Simple and Effective Method for Text Clustering. Natural Language Engineering. 1-40. https://doi.org/10.1017/S1351324915000273S140Zhao, Y., & Karypis, G. (2004). Empirical and Theoretical Comparisons of Selected Criterion Functions for Document Clustering. Machine Learning, 55(3), 311-331. doi:10.1023/b:mach.0000027785.44527.d6Tu, L., & Chen, Y. (2009). Stream data clustering based on grid density and attraction. ACM Transactions on Knowledge Discovery from Data, 3(3), 1-27. doi:10.1145/1552303.1552305Yang, T., Jin, R., Chi, Y., & Zhu, S. (2009). Combining link and content for community detection. Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD ’09. doi:10.1145/1557019.1557120Zhao, Y., Karypis, G., & Fayyad, U. (2005). Hierarchical Clustering Algorithms for Document Datasets. Data Mining and Knowledge Discovery, 10(2), 141-168. doi:10.1007/s10618-005-0361-3Kaufman, L., & Rousseeuw, P. J. (Eds.). (1990). Finding Groups in Data. Wiley Series in Probability and Statistics. doi:10.1002/9780470316801Karypis, G., Eui-Hong Han, & Kumar, V. (1999). Chameleon: hierarchical clustering using dynamic modeling. Computer, 32(8), 68-75. doi:10.1109/2.781637Cagnina, L., Errecalde, M., Ingaramo, D., & Rosso, P. (2014). An efficient Particle Swarm Optimization approach to cluster short texts. Information Sciences, 265, 36-49. doi:10.1016/j.ins.2013.12.010He, H., Chen, B., Xu, W., & Guo, J. (2007). Short Text Feature Extraction and Clustering for Web Topic Mining. Third International Conference on Semantics, Knowledge and Grid (SKG 2007). doi:10.1109/skg.2007.76Spearman, C. (1904). The Proof and Measurement of Association between Two Things. The American Journal of Psychology, 15(1), 72. doi:10.2307/1412159Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53-65. doi:10.1016/0377-0427(87)90125-7Manning, C. D., Raghavan, P., & Schutze, H. (2008). Introduction to Information Retrieval. doi:10.1017/cbo9780511809071Qi, G.-J., Aggarwal, C. C., & Huang, T. (2012). Community Detection with Edge Content in Social Media Networks. 2012 IEEE 28th International Conference on Data Engineering. doi:10.1109/icde.2012.77Daxin Jiang, Jian Pei, & Aidong Zhang. (s. f.). DHC: a density-based hierarchical clustering method for time series gene expression data. Third IEEE Symposium on Bioinformatics and Bioengineering, 2003. Proceedings. doi:10.1109/bibe.2003.1188978Charikar, M., Chekuri, C., Feder, T., & Motwani, R. (2004). Incremental Clustering and Dynamic Information Retrieval. SIAM Journal on Computing, 33(6), 1417-1440. doi:10.1137/s0097539702418498Selim, S. Z., & Alsultan, K. (1991). A simulated annealing algorithm for the clustering problem. Pattern Recognition, 24(10), 1003-1008. doi:10.1016/0031-3203(91)90097-oAranganayagi, S., & Thangavel, K. (2007). Clustering Categorical Data Using Silhouette Coefficient as a Relocating Measure. International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007). doi:10.1109/iccima.2007.328Makagonov, P., Alexandrov, M., & Gelbukh, A. (2004). Clustering Abstracts Instead of Full Texts. Lecture Notes in Computer Science, 129-135. doi:10.1007/978-3-540-30120-2_17Jing L. 2005. Survey of text clustering. Technical report. Department of Mathematics. The University of Hong Kong, Hong Kong, China.Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27(3), 379-423. doi:10.1002/j.1538-7305.1948.tb01338.xHearst, M. A. (2006). Clustering versus faceted categories for information exploration. Communications of the ACM, 49(4), 59. doi:10.1145/1121949.1121983Alexandrov, M., Gelbukh, A., & Rosso, P. (2005). An Approach to Clustering Abstracts. Lecture Notes in Computer Science, 275-285. doi:10.1007/11428817_25Dos Santos, J. B., Heuser, C. A., Moreira, V. P., & Wives, L. K. (2011). Automatic threshold estimation for data matching applications. Information Sciences, 181(13), 2685-2699. doi:10.1016/j.ins.2010.05.029Hasan, M. A., Chaoji, V., Salem, S., & Zaki, M. J. (2009). Robust partitional clustering by outlier and density insensitive seeding. Pattern Recognition Letters, 30(11), 994-1002. doi:10.1016/j.patrec.2009.04.013Dunn†, J. C. (1974). Well-Separated Clusters and Optimal Fuzzy Partitions. Journal of Cybernetics, 4(1), 95-104. doi:10.1080/01969727408546059Carullo, M., Binaghi, E., & Gallo, I. (2009). An online document clustering technique for short web contents. Pattern Recognition Letters, 30(10), 870-876. doi:10.1016/j.patrec.2009.04.001Kruskal, W. H., & Wallis, W. A. (1952). Use of Ranks in One-Criterion Variance Analysis. Journal of the American Statistical Association, 47(260), 583-621. doi:10.1080/01621459.1952.10483441Bezdek, J. C., & Pal, N. R. (s. f.). Cluster validation with generalized Dunn’s indices. Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems. doi:10.1109/annes.1995.499469Brun, M., Sima, C., Hua, J., Lowey, J., Carroll, B., Suh, E., & Dougherty, E. R. (2007). Model-based evaluation of clustering validation measures. Pattern Recognition, 40(3), 807-824. doi:10.1016/j.patcog.2006.06.026Davies, D. L., & Bouldin, D. W. (1979). A Cluster Separation Measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-1(2), 224-227. doi:10.1109/tpami.1979.4766909Pinto, D., & Rosso, P. (s. f.). On the Relative Hardness of Clustering Corpora. Lecture Notes in Computer Science, 155-161. doi:10.1007/978-3-540-74628-7_22Pons-Porrata, A., Berlanga-Llavori, R., & Ruiz-Shulcloper, J. (2007). Topic discovery based on text mining techniques. Information Processing & Management, 43(3), 752-768. doi:10.1016/j.ipm.2006.06.001Pinto, D., Benedí, J.-M., & Rosso, P. (2007). Clustering Narrow-Domain Short Texts by Using the Kullback-Leibler Distance. Lecture Notes in Computer Science, 611-622. doi:10.1007/978-3-540-70939-8_5

Aberrant Herpesvirus-Induced Polyadenylation Correlates With Cellular Messenger RNA Destruction

Inhibition of host cell gene expression by the human herpesvirus KSHV occurs via a novel mechanism involving polyadenylation-linked RNA turnover

Is prolonged infusion of piperacillin/tazobactam and meropenem in critically ill patients associated with improved pharmacokinetic/pharmacodynamic and patient outcomes? An observation from the Defining Antibiotic Levels in Intensive care unit patients (DALI) cohort

Objectives:We utilized the database of the Defining Antibiotic Levels in Intensive care unit patients (DALI) study to statistically compare the pharmacokinetic/pharmacodynamic and clinical outcomes between prolonged-infusion and intermittent-bolus dosing of piperacillin/tazobactam and meropenem in critically ill patients using inclusion criteria similar to those used in previous prospective studies.Methods: This was a post hoc analysis of a prospective, multicentre pharmacokinetic point-prevalence study (DALI), which recruited a large cohort of critically ill patients from 68 ICUs across 10 countries.Results: Of the 211 patients receiving piperacillin/tazobactam and meropenem in the DALI study, 182 met inclusion criteria. Overall, 89.0% (162/182) of patients achieved the most conservative target of 50% fT(&gt; MIC) (time over which unbound or free drug concentration remains above the MIC). Decreasing creatinine clearance and the use of prolonged infusion significantly increased the PTA for most pharmacokinetic/pharmacodynamic targets. In the subgroup of patients who had respiratory infection, patients receiving beta-lactams via prolonged infusion demonstrated significantly better 30 day survival when compared with intermittent-bolus patients [86.2% (25/29) versus 56.7% (17/30); P=0.012]. Additionally, in patients with a SOFA score of &gt;= 9, administration by prolonged infusion compared with intermittent-bolus dosing demonstrated significantly better clinical cure [73.3% (11/15) versus 35.0% (7/20); P=0.035] and survival rates [73.3% (11/15) versus 25.0% (5/20); P=0.025].Conclusions: Analysis of this large dataset has provided additional data on the niche benefits of administration of piperacillin/tazobactam and meropenem by prolonged infusion in critically ill patients, particularly for patients with respiratory infections

Improving our understanding of the in vivo modelling of psychotic disorders: a systematic review and meta-analysis

Psychotic disorders represent a severe category of mental disorders affecting about one percent of the population. Individuals experience a loss or distortion of contact with reality alongside other symptoms, many of which are still not adequately managed using existing treatments. While animal models of these disorders could offer insights into these disorders and potential new treatments, translation of this knowledge has so far been poor in terms of informing clinical trials and practice. The aim of this project was to improve our understanding of these pre-clinical studies and identify potential weaknesses underlying translational failure. I carried out a systematic search of the literature to provide an unbiased summary of publications reporting animal models of schizophrenia and other psychotic disorders. From these publications, data were extracted to quantify aspects of the field including reported quality of studies, study characteristics and behavioural outcome data. The latter of these data were then used to calculate estimates of efficacy using random-effects meta-analysis. Having identified 3847 publications of relevance, including 852 different methods used to induce the model, over 359 different outcomes tested in them and almost 946 different treatments reported to be administered. I show that a large proportion of studies use simple pharmacological interventions to induce their models of these disorders, despite the availability of models using other interventions that are arguably of higher translational relevance. I also show that the reported quality of these studies is low, and only 22% of studies report taking measures to reduce the risk of biases such as randomisation and blinding, which has been shown to affect the reliability of results drawn. Through this work it becomes apparent that the literature is incredibly vast for studies looking at animal models of psychotic disorders and that some of the relevant work potentially overlaps with studies describing other conditions. This means that drawing reliable conclusions from these data is affected by what is made available in the literature, how it is reported and identified in a search and the time that it takes to reach these conclusions. I introduce the idea of using computer-assisted tools to overcome one of these problems in the long term. Translation of results from studies looking at animals modelling uniquely-human psychotic disorders to clinical successes might be improved by better reporting of studies including publishing of all work carried out, labelling of studies more uniformly so that it is identifiable, better reporting of study design including improving on reporting of measures taken to reduce the risk of bias and focusing on models with greater validity to the human condition

A Validated Age-Related Normative Model for Male Total Testosterone Shows Increasing Variance but No Decline after Age 40 Years

The diagnosis of hypogonadism in human males includes identification of low serum testosterone levels, and hence there is an underlying assumption that normal ranges of testosterone for the healthy population are known for all ages. However, to our knowledge, no such reference model exists in the literature, and hence the availability of an applicable biochemical reference range would be helpful for the clinical assessment of hypogonadal men. In this study, using model selection and validation analysis of data identified and extracted from thirteen studies, we derive and validate a normative model of total testosterone across the lifespan in healthy men. We show that total testosterone peaks [mean (2.5-97.5 percentile)] at 15.4 (7.2-31.1) nmol/L at an average age of 19 years, and falls in the average case [mean (2.5-97.5 percentile)] to 13.0 (6.6-25.3) nmol/L by age 40 years, but we find no evidence for a further fall in mean total testosterone with increasing age through to old age. However we do show that there is an increased variation in total testosterone levels with advancing age after age 40 years. This model provides the age related reference ranges needed to support research and clinical decision making in males who have symptoms that may be due to hypogonadism.Publisher PDFPeer reviewe