Multinuclear ruthenium(II) complexes as anticancer agents

A series of dinuclear ruthenium(ii) complexes that contain labile chlorido ligands, [{Ru(tpy)Cl}2{μ-bbn}]2+ {designated Cl-Rubbn; tpy = 2,2′:6′,2′′-terpyridine, bbn = bis[4(4′-methyl-2,2′-bipyridyl)]-1,n-alkane (n = 7, 10, 12, 14 or 16)} and derivatives containing nitro substituents on the tpy ligand and/or secondary amines within the bbn linking chain have been synthesised and their potential as anticancer agents examined. Some of the Cl-Rubbn species showed good anticancer activity against MCF-7 and MDA-MB-231 breast cancer cell lines, with the Cl-Rubb12 complex being four-times more active than cisplatin. Inclusion of nitro substituents on the tpy ligands of Cl-Rubb12 resulted in significantly decreased anticancer activity. The incorporation of amine groups into the linking ligand did not increase the anticancer activity of the Cl-Rubbn complexes. The Cl-Rubbn complexes and those containing amine groups in the linking chain aquated at approximately the same rate, with 50% aquation within 120 minutes. By comparison, the complexes containing nitro substituents on the tpy ligand aquated extremely slowly, with 60% of the chlorido complex remaining 24 hours after they were dissolved in water. Cyclic voltammetry with the model mononuclear complex [Ru{(NO2)3tpy}(Me2bpy)Cl] + {(NO2)3tpy = 4,4′,4′′- trinitro-2,2′:6′,2′′-terpyridine} showed that the nitro substituents exerted a strong effect on the ruthenium centre, with the anodic peak corresponding to the Ru(iii/ii) couple shifted positively by 300 mV compared to that from the non-nitrated parent complex [Ru(tpy)(Me 2bpy)Cl]+. 1H NMR studies of the reaction of the Cl-Rubbn complexes with GMP indicated that the ruthenium complexes covalently bound the nucleotide slowly, with 33% bound in 24 hours. However, the results of this study suggest that the cytotoxicity of the dinuclear ruthenium complexes is a combination of covalent and reversible binding with DNA. © the Partner Organisations 2014

Urbanization and Green Spaces—A Study on Jnana Bharathi Campus, Bangalore University

Global warming is amongst the most alarming problems of the new era. Carbon emission is evidently the strongest fundamental factor for global warming. So increasing carbon emission is one of today’s major concerns, which is well addressed in the Kyoto Protocol. Trees are amongst the most significant elements of any landscape, because of both biomass and diversity, and their key role in ecosystem dynamics is well known. Trees absorb the atmospheric carbon dioxide and act as a carbon sink, since 50 % of biomass is carbon itself and the importance of carbon sequestration in forest areas is already accepted, and well documented. With this background, a carbon sequestration potential study was carried out in Jnana Bharathi campus, Bangalore University using the Quadrat method. The total geographical area is about 449.74 ha with a rich vegetation sector and the total amount of both above ground carbon (AGC) and below ground carbon (BGC) was estimated as an average of 54.8 t/ha. The total amount of carbon dioxide assimilated into the vegetation in terms of both above ground and below ground biomass was estimated as an average of 200.9 t/ha. Urbanization and habitat fragmentation seem to be increasing worldwide, substantiated by a case study in Bangalore City. The analysis revealed that increase in built-up area at the city level was by about 164.62 km2, while the vegetation and water bodies decreased by about 285.72 and 7.2 km2 respectively. However, Bangalore University, Jnana Bharathi campus attains a good vegetation cover and is seen as one of the ‘green lungs’ of Bangalore city

Dendritic Spine Shape Analysis: A Clustering Perspective

Functional properties of neurons are strongly coupled with their morphology. Changes in neuronal activity alter morphological characteristics of dendritic spines. First step towards understanding the structure-function relationship is to group spines into main spine classes reported in the literature. Shape analysis of dendritic spines can help neuroscientists understand the underlying relationships. Due to unavailability of reliable automated tools, this analysis is currently performed manually which is a time-intensive and subjective task. Several studies on spine shape classification have been reported in the literature, however, there is an on-going debate on whether distinct spine shape classes exist or whether spines should be modeled through a continuum of shape variations. Another challenge is the subjectivity and bias that is introduced due to the supervised nature of classification approaches. In this paper, we aim to address these issues by presenting a clustering perspective. In this context, clustering may serve both confirmation of known patterns and discovery of new ones. We perform cluster analysis on two-photon microscopic images of spines using morphological, shape, and appearance based features and gain insights into the spine shape analysis problem. We use histogram of oriented gradients (HOG), disjunctive normal shape models (DNSM), morphological features, and intensity profile based features for cluster analysis. We use x-means to perform cluster analysis that selects the number of clusters automatically using the Bayesian information criterion (BIC). For all features, this analysis produces 4 clusters and we observe the formation of at least one cluster consisting of spines which are difficult to be assigned to a known class. This observation supports the argument of intermediate shape types.Comment: Accepted for BioImageComputing workshop at ECCV 201

The Changing Epidemiology of Murray Valley Encephalitis in Australia: The 2011 Outbreak and a Review of the Literature

Murray Valley encephalitis virus (MVEV) is the most serious of the endemic arboviruses in Australia. It was responsible for six known large outbreaks of encephalitis in south-eastern Australia in the 1900s, with the last comprising 58 cases in 1974. Since then MVEV clinical cases have been largely confined to the western and central parts of northern Australia. In 2011, high-level MVEV activity occurred in south-eastern Australia for the first time since 1974, accompanied by unusually heavy seasonal MVEV activity in northern Australia. This resulted in 17 confirmed cases of MVEV disease across Australia. Record wet season rainfall was recorded in many areas of Australia in the summer and autumn of 2011. This was associated with significant flooding and increased numbers of the mosquito vector and subsequent MVEV activity. This paper documents the outbreak and adds to our knowledge about disease outcomes, epidemiology of disease and the link between the MVEV activity and environmental factors. Clinical and demographic information from the 17 reported cases was obtained. Cases or family members were interviewed about their activities and location during the incubation period. In contrast to outbreaks prior to 2000, the majority of cases were non-Aboriginal adults, and almost half (40%) of the cases acquired MVEV outside their area of residence. All but two cases occurred in areas of known MVEV activity.This outbreak continues to reflect a change in the demographic pattern of human cases of encephalitic MVEV over the last 20 years. In northern Australia, this is associated with the increasing numbers of non-Aboriginal workers and tourists living and travelling in endemic and epidemic areas, and also identifies an association with activities that lead to high mosquito exposure. This outbreak demonstrates that there is an ongoing risk of MVEV encephalitis to the heavily populated areas of south-eastern Australia

Locomotor constraints favour the evolution of the human pygmy phenotype in tropical rainforests.

The convergent evolution of the human pygmy phenotype in tropical rainforests is widely assumed to reflect adaptation in response to the distinct ecological challenges of this habitat (e.g. high levels of heat and humidity, high pathogen load, low food availability, and dense forest structure), yet few precise adaptive benefits of this phenotype have been proposed. Here, we describe and test a biomechanical model of how the rainforest environment can alter gait kinematics such that short stature is advantageous in dense habitats. We hypothesized that environmental constraints on step length in rainforests alter walking mechanics such that taller individuals are expected to walk more slowly due to their inability to achieve preferred step lengths in the rainforest. We tested predictions from this model with experimental field data from two short-statured populations that regularly forage in the rainforest: the Batek of Peninsular Malaysia and the Tsimane of the Bolivian Amazon. In accordance with model expectations, we found stature-dependent constraints on step length in the rainforest and concomitant reductions in walking speed that are expected to compromise foraging efficiency. These results provide the first evidence that the human pygmy phenotype is beneficial in terms of locomotor performance and highlight the value of applying laboratory-derived biomechanical models to field settings for testing evolutionary hypotheses

SMART: Unique splitting-while-merging framework for gene clustering

Copyright @ 2014 Fa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Successful clustering algorithms are highly dependent on parameter settings. The clustering performance degrades significantly unless parameters are properly set, and yet, it is difficult to set these parameters a priori. To address this issue, in this paper, we propose a unique splitting-while-merging clustering framework, named “splitting merging awareness tactics” (SMART), which does not require any a priori knowledge of either the number of clusters or even the possible range of this number. Unlike existing self-splitting algorithms, which over-cluster the dataset to a large number of clusters and then merge some similar clusters, our framework has the ability to split and merge clusters automatically during the process and produces the the most reliable clustering results, by intrinsically integrating many clustering techniques and tasks. The SMART framework is implemented with two distinct clustering paradigms in two algorithms: competitive learning and finite mixture model. Nevertheless, within the proposed SMART framework, many other algorithms can be derived for different clustering paradigms. The minimum message length algorithm is integrated into the framework as the clustering selection criterion. The usefulness of the SMART framework and its algorithms is tested in demonstration datasets and simulated gene expression datasets. Moreover, two real microarray gene expression datasets are studied using this approach. Based on the performance of many metrics, all numerical results show that SMART is superior to compared existing self-splitting algorithms and traditional algorithms. Three main properties of the proposed SMART framework are summarized as: (1) needing no parameters dependent on the respective dataset or a priori knowledge about the datasets, (2) extendible to many different applications, (3) offering superior performance compared with counterpart algorithms.National Institute for Health Researc

Intercomparison of the northern hemisphere winter mid-latitude atmospheric variability of the IPCC models

We compare, for the overlapping time frame 1962-2000, the estimate of the northern hemisphere (NH) mid-latitude winter atmospheric variability within the XX century simulations of 17 global climate models (GCMs) included in the IPCC-4AR with the NCEP and ECMWF reanalyses. We compute the Hayashi spectra of the 500hPa geopotential height fields and introduce an integral measure of the variability observed in the NH on different spectral sub-domains. Only two high-resolution GCMs have a good agreement with reanalyses. Large biases, in most cases larger than 20%, are found between the wave climatologies of most GCMs and the reanalyses, with a relative span of around 50%. The travelling baroclinic waves are usually overestimated, while the planetary waves are usually underestimated, in agreement with previous studies performed on global weather forecasting models. When comparing the results of various versions of similar GCMs, it is clear that in some cases the vertical resolution of the atmosphere and, somewhat unexpectedly, of the adopted ocean model seem to be critical in determining the agreement with the reanalyses. The GCMs ensemble is biased with respect to the reanalyses but is comparable to the best 5 GCMs. This study suggests serious caveats with respect to the ability of most of the presently available GCMs in representing the statistics of the global scale atmospheric dynamics of the present climate and, a fortiori, in the perspective of modelling climate change.Comment: 39 pages, 8 figures, 2 table

Why is it difficult to implement e-health initiatives? A qualitative study

<b>Background</b> The use of information and communication technologies in healthcare is seen as essential for high quality and cost-effective healthcare. However, implementation of e-health initiatives has often been problematic, with many failing to demonstrate predicted benefits. This study aimed to explore and understand the experiences of implementers - the senior managers and other staff charged with implementing e-health initiatives and their assessment of factors which promote or inhibit the successful implementation, embedding, and integration of e-health initiatives.<p></p> <b>Methods</b> We used a case study methodology, using semi-structured interviews with implementers for data collection. Case studies were selected to provide a range of healthcare contexts (primary, secondary, community care), e-health initiatives, and degrees of normalization. The initiatives studied were Picture Archiving and Communication System (PACS) in secondary care, a Community Nurse Information System (CNIS) in community care, and Choose and Book (C&B) across the primary-secondary care interface. Implementers were selected to provide a range of seniority, including chief executive officers, middle managers, and staff with 'on the ground' experience. Interview data were analyzed using a framework derived from Normalization Process Theory (NPT).<p></p> <b>Results</b> Twenty-three interviews were completed across the three case studies. There were wide differences in experiences of implementation and embedding across these case studies; these differences were well explained by collective action components of NPT. New technology was most likely to 'normalize' where implementers perceived that it had a positive impact on interactions between professionals and patients and between different professional groups, and fit well with the organisational goals and skill sets of existing staff. However, where implementers perceived problems in one or more of these areas, they also perceived a lower level of normalization.<p></p> <b>Conclusions</b> Implementers had rich understandings of barriers and facilitators to successful implementation of e-health initiatives, and their views should continue to be sought in future research. NPT can be used to explain observed variations in implementation processes, and may be useful in drawing planners' attention to potential problems with a view to addressing them during implementation planning