Attributed relational graphs for cell nucleus segmentation in fluorescence microscopy Images

Cataloged from PDF version of article.More rapid and accurate high-throughput screening in molecular cellular biology research has become possible with the development of automated microscopy imaging, for which cell nucleus segmentation commonly constitutes the core step. Although several promising methods exist for segmenting the nuclei of monolayer isolated and less-confluent cells, it still remains an open problem to segment the nuclei of more-confluent cells, which tend to grow in overlayers. To address this problem, we propose a new model-based nucleus segmentation algorithm. This algorithm models how a human locates a nucleus by identifying the nucleus boundaries and piecing them together. In this algorithm, we define four types of primitives to represent nucleus boundaries at different orientations and construct an attributed relational graph on the primitives to represent their spatial relations. Then, we reduce the nucleus identification problem to finding predefined structural patterns in the constructed graph and also use the primitives in region growing to delineate the nucleus borders. Working with fluorescence microscopy images, our experiments demonstrate that the proposed algorithm identifies nuclei better than previous nucleus segmentation algorithms

Transfer learning for drug–target interaction prediction

MotivationUtilizing AI-driven approaches for drug–target interaction (DTI) prediction require large volumes of training data which are not available for the majority of target proteins. In this study, we investigate the use of deep transfer learning for the prediction of interactions between drug candidate compounds and understudied target proteins with scarce training data. The idea here is to first train a deep neural network classifier with a generalized source training dataset of large size and then to reuse this pre-trained neural network as an initial configuration for re-training/fine-tuning purposes with a small-sized specialized target training dataset. To explore this idea, we selected six protein families that have critical importance in biomedicine: kinases, G-protein-coupled receptors (GPCRs), ion channels, nuclear receptors, proteases, and transporters. In two independent experiments, the protein families of transporters and nuclear receptors were individually set as the target datasets, while the remaining five families were used as the source datasets. Several size-based target family training datasets were formed in a controlled manner to assess the benefit provided by the transfer learning approach.ResultsHere, we present a systematic evaluation of our approach by pre-training a feed-forward neural network with source training datasets and applying different modes of transfer learning from the pre-trained source network to a target dataset. The performance of deep transfer learning is evaluated and compared with that of training the same deep neural network from scratch. We found that when the training dataset contains fewer than 100 compounds, transfer learning outperforms the conventional strategy of training the system from scratch, suggesting that transfer learning is advantageous for predicting binders to under-studied targets.Availability and implementationThe source code and datasets are available at https://github.com/cansyl/TransferLearning4DTI. Our web-based service containing the ready-to-use pre-trained models is accessible at https://tl4dti.kansil.org

Data and model driven hybrid approach to activity scoring of cyclic pathways

Analysis of large scale -omics data based on a single tool remains inefficient to reveal molecular basis of cellular events. Therefore, data integration from multiple heterogeneous sources is highly desirable and required. In this study, we developed a data- and model-driven hybrid approach to evaluate biological activity of cellular processes. Biological pathway models were taken as graphs and gene scores were transferred through neighbouring nodes of these graphs. An activity score describes the behaviour of a specific biological process was computed by owing of converged gene scores until reaching a target process. Biological pathway model based approach that we describe in this study is a novel approach in which converged scores are calculated for the cellular processes of a cyclic pathway. The convergence of the activity scores for cyclic graphs were demonstrated on the KEGG pathways. © 2011 Springer Science+Business Media B.V

Capacity Building in Global Mental Health: Professional Training

We suggest that the optimal approach to building capacity in global mental health care will require partnerships between professional resources in high-income countries and promising health-related institutions in low- and middle-income countries. The result of these partnerships will be sustainable academic relationships that can educate a new generation of in-country primary care physicians and, eventually, specialized health professionals. Research capabilities will be an essential educational component to inform policy and practice, and to ensure careful outcome measurements of training and of intervention, prevention, and promotion strategies. The goal of these academic centers of excellence will be to develop quality, in-country clinical and research professionals, and to build a productive environment for these professionals to advance their careers locally. In sum, this article discusses human capacity building in global mental health, provides recommendations for training, and offers examples of recent initiatives. (Harv Rev Psychiatry 2012;20:47–57.

URBAN MODELLING PERFORMANCE OF NEXT GENERATION SAR MISSIONS

In synthetic aperture radar (SAR) technology, urban mapping and modelling have become possible with revolutionary missions TerraSAR-X (TSX) and Cosmo-SkyMed (CSK) since 2007. These satellites offer 1m spatial resolution in high-resolution spotlight imaging mode and capable for high quality digital surface model (DSM) acquisition for urban areas utilizing interferometric SAR (InSAR) technology. With the advantage of independent generation from seasonal weather conditions, TSX and CSK DSMs are much in demand by scientific users. The performance of SAR DSMs is influenced by the distortions such as layover, foreshortening, shadow and double-bounce depend up on imaging geometry. In this study, the potential of DSMs derived from convenient 1m high-resolution spotlight (HS) InSAR pairs of CSK and TSX is validated by model-to-model absolute and relative accuracy estimations in an urban area. For the verification, an airborne laser scanning (ALS) DSM of the study area was used as the reference model. Results demonstrated that TSX and CSK urban DSMs are compatible in open, built-up and forest land forms with the absolute accuracy of 8–10 m. The relative accuracies based on the coherence of neighbouring pixels are superior to absolute accuracies both for CSK and TSX

The Design and Cytotoxic Evaluation of Some 1-Aryl-3- isopropylamino-1-propanone Hydrochlorides towards Human Huh-7 Hepatoma Cells

Cataloged from PDF version of article.A series of 1-aryl-3-isopropylamino-1-propanone hydrochlorides 1 and a related heterocyclic analog 2 as candidate antineoplastic agents were prepared and the rationale for designing these compounds is presented. A specific objective in this study is the discovery of novel compounds possessing growth-inhibiting properties of hepatoma cells. The compounds in series 1 and 2 were prepared and their structures established unequivocally. X-ray crystallography of two representative compounds 1d and 1g were achieved. Over half of the compounds are more potent than 5-fluorouracil which is an established drug used in treating liver cancers. QSAR evaluations and molecular modeling studies were undertaken with a view to detecting some physicochemical parameters which govern cytotoxic potencies. A number of guidelines for amplification of the project have been formulated. A number of Mannich bases displayed greater potency than the reference drug 5-fluorouracil against human Huh-7 hepatoma cells. In particular, 1i emerged as a lead compound possessing 2.8 fold higher activity than that of the reference drug. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

A small library of chalcones induce liver cancer cell death through Akt phosphorylation inhibition

Hepatocellular carcinoma (HCC) ranks as the fifth most common and the second deadliest cancer worldwide. HCC is extremely resistant to the conventional chemotherapeutics. Hence, it is vital to develop new treatment options. Chalcones were previously shown to have anticancer activities in other cancer types. In this study, 11 chalcones along with quercetin, papaverin, catechin, Sorafenib and 5FU were analyzed for their bioactivities on 6 HCC cell lines and on dental pulp stem cells (DPSC) which differentiates into hepatocytes, and is used as a model for untransformed control cells. 3 of the chalcones (1, 9 and 11) were selected for further investigation due to their high cytotoxicity against liver cancer cells and compared to the other clinically established compounds. Chalcones did not show significant bioactivity ([Formula: see text]) on dental pulp stem cells. Cell cycle analysis revealed that these 3 chalcone-molecules induced SubG1/G1 arrest. Akt protein phosphorylation was inhibited by these molecules in PTEN deficient, drug resistant, mesenchymal like Mahlavu cells leading to the activation of p21 and the inhibition of NF[Formula: see text]B-p65 transcription factor. Hence the chalcones induced apoptotic cell death pathway through NF[Formula: see text]B-p65 inhibition. On the other hand, these molecules triggered p21 dependent activation of Rb protein and thereby inhibition of cell cycle and cell growth in liver cancer cells. Involvement of PI3K/Akt pathway hyperactivation was previously described in survival of liver cancer cells as carcinogenic event. Therefore, our results indicated that these chalcones can be considered as candidates for liver cancer therapeutics particularly when PI3K/Akt pathway involved in tumor development

A novel form of recessive limb girdle muscular dystrophy with mental retardation and abnormal expression of alpha-dystroglycan

Cataloged from PDF version of article.The limb girdle muscular dystrophies are a heterogeneous group of conditions characterized by proximal muscle weakness and disease onset ranging from infancy to adulthood. We report here eight patients from seven unrelated families affected by a novel and relatively mild form of autosomal recessive limb girdle muscular dystrophy (LGMD2) with onset in the first decade of life and characterized by severe mental retardation but normal brain imaging. Immunocytochemical studies revealed a significant selective reduction of α-dystroglycan expression in the muscle biopsies. Linkage analysis excluded known loci for both limb girdle muscular dystrophy and congenital muscular dystrophies in the consanguineous families. We consider that this represents a novel form of muscular dystrophy with associated brain involvement. The biochemical studies suggest that it may belong to the growing number of muscular dystrophies with abnormal expression of α-dystroglycan. © 2003 Published by Elsevier B.V

Effects of muscular dystrophy, exercise and blocking activin receptor IIB ligands on the unfolded protein response and oxidative stress

Protein homeostasis in cells, proteostasis, is maintained through several integrated processes and pathways and its dysregulation may mediate pathology in many diseases including Duchenne muscular dystrophy (DMD). Oxidative stress, heat shock proteins, endoplasmic reticulum (ER) stress and its response, i.e. unfolded protein response (UPR), play key roles in proteostasis but their involvement in the pathology of DMD are largely unknown. Moreover, exercise and activin receptor IIB blocking are two strategies that may be beneficial to DMD muscle, but studies to examine their effects on these proteostasis pathways are lacking. Therefore, these pathways were examined in the muscle of mdx mice, a model of DMD, under basal conditions and in response to seven weeks of voluntary exercise and/or activin receptor IIB ligand blocking using soluble activin receptor-Fc (sAcvR2B-Fc) administration. In conjunction with reduced muscle strength, mdx muscle displayed greater levels of UPR/ER-pathway indicators including greater protein levels of IREloc, PERK and Atf6b mRNA. Downstream to IREloc and PERK, spliced Xbpl mRNA and phosphorylation of elF2oc, were also increased. Most of the cytoplasmic and ER chaperones and mitochondrial UPR markers were unchanged in mdx muscle. Oxidized glutathione was greater in mdx and was associated with increases in lysine acetylated proteome and phosphorylated sirtuin 1. Exercise increased oxidative stress when performed independently or combined with sAcvR2B-Fc administration. Although neither exercise nor sAcvR2B-Fc administration imparted a clear effect on ER stress/UPR pathways or heat shock proteins, sAcvR2B-Fc administration increased protein expression levels of GRP78/BiP, a triggering factor for ER stress/UPR activation and TxNIP, a redox-regulator of ER stress-induced inflammation. In conclusion, the ER stress and UPR are increased in mdx muscle. However, these processes are not distinctly improved by voluntary exercise or blocking activin receptor IIB ligands and thus do not appear to be optimal therapeutic choices for improving proteostasis in DMD. (C) 2016 Elsevier Inc. All rights reserved.Peer reviewe

Modeling resilience and sustainability in ancient agricultural systems

The reasons why people adopt unsustainable agricultural practices, and the ultimate environmental implications of those practices, remain incompletely understood in the present world. Archaeology, however, offers unique datasets on coincident cultural and ecological change, and their social and environmental effects. This article applies concepts derived from ecological resilience thinking to assess the sustainability of agricultural practices as a result of long-term interactions between political, economic, and environmental systems. Using the urban center of Gordion, in central Turkey, as a case study, it is possible to identify mismatched social and ecological processes on temporal, spatial, and organizational scales, which help to resolve thresholds of resilience. Results of this analysis implicate temporal and spatial mismatches as a cause for local environmental degradation, and increasing extralocal economic pressures as an ultimate cause for the adoption of unsustainable land-use practices. This analysis suggests that a research approach that integrates environmental archaeology with a resilience perspective has considerable potential for explicating regional patterns of agricultural change and environmental degradation in the past