Second-line treatment for primary central nervous system lymphoma

Failure after first-line treatment was reported in 35–60% of immunocompetent patients with primary central nervous system lymphoma (PCNSL). There are currently no reports focusing on salvage therapy. This review analyses prognostic factors and the efficacy of salvage therapy by focusing on data from papers reporting results of first-line treatment in 355 cases. The study group consisted of 173 patients presenting treatment failure. The interval between failure and death (TTD) was compared for age at relapse (≤60 vs >60 years), type of failure (relapse vs progression), time to relapse (≤12 vs >12 months) and salvage treatment (yes vs no). Median TTD was similar in younger and older patients (P = 0.09). Relapsed patients had a longer TTD than patients with progressive disease (P = 0.002). Early relapse led to a shorter TTD than late relapse (P = 0.005). Median TTD was 14 months for patients who underwent salvage therapy and 2 months for untreated cases (P < 0.00001). A multivariate analysis showed an independent prognostic role for salvage therapy and time to relapse. Age and type of failure had no predictive value. Salvage therapy significantly improves outcome and, possibly, quality of life. As many different treatments were used conclusions cannot be made regarding an optimal treatment schedule. © 1999 Cancer Research Campaig

Targeting Huntington’s disease through histone deacetylases

Huntington’s disease (HD) is a debilitating neurodegenerative condition with significant burdens on both patient and healthcare costs. Despite extensive research, treatment options for patients with this condition remain limited. Aberrant post-translational modification (PTM) of proteins is emerging as an important element in the pathogenesis of HD. These PTMs include acetylation, phosphorylation, methylation, sumoylation and ubiquitination. Several families of proteins are involved with the regulation of these PTMs. In this review, I discuss the current evidence linking aberrant PTMs and/or aberrant regulation of the cellular machinery regulating these PTMs to HD pathogenesis. Finally, I discuss the evidence suggesting that pharmacologically targeting one of these protein families the histone deacetylases may be of potential therapeutic benefit in the treatment of HD

Predictive modelling of soils’ hydraulic conductivity using artificial neural network and multiple linear regression

As a result of heterogeneity nature of soils and variation in its hydraulic conductivity over several orders of magnitude for various soil types from fine-grained to coarse-grained soils, predictive methods to estimate hydraulic conductivity of soils from properties considered more easily obtainable have now been given an appropriate consideration. This study evaluates the performance of artificial neural network (ANN) being one of the popular computational intelligence techniques in predicting hydraulic conductivity of wide range of soil types and compared with the traditional multiple linear regression (MLR). ANN and MLR models were developed using six input variables. Results revealed that only three input variables were statistically significant in MLR model development. Performance evaluations of the developed models using determination coefficient and mean square error show that the prediction capability of ANN is far better than MLR. In addition, comparative study with available existing models shows that the developed ANN and MLR in this study performed relatively better