Investigating antimalarial drug interactions of emetine dihydrochloride hydrate using CalcuSyn-based interactivity calculations

The widespread introduction of artemisinin-based combination therapy has contributed to recent reductions in malaria mortality. Combination therapies have a range of advantages, including synergism, toxicity reduction, and delaying the onset of resistance acquisition. Unfortunately, antimalarial combination therapy is limited by the depleting repertoire of effective drugs with distinct target pathways. To fast-track antimalarial drug discovery, we have previously employed drug-repositioning to identify the anti-amoebic drug, emetine dihydrochloride hydrate, as a potential candidate for repositioned use against malaria. Despite its 1000-fold increase in in vitro antimalarial potency (ED50 47 nM) compared with its anti-amoebic potency (ED50 26±32 uM), practical use of the compound has been limited by dose-dependent toxicity (emesis and cardiotoxicity). Identification of a synergistic partner drug would present an opportunity for dose-reduction, thus increasing the therapeutic window. The lack of reliable and standardised methodology to enable the in vitro definition of synergistic potential for antimalarials is a major drawback. Here we use isobologram and combination-index data generated by CalcuSyn software analyses (Biosoft v2.1) to define drug interactivity in an objective, automated manner. The method, based on the median effect principle proposed by Chou and Talalay, was initially validated for antimalarial application using the known synergistic combination (atovaquone-proguanil). The combination was used to further understand the relationship between SYBR Green viability and cytocidal versus cytostatic effects of drugs at higher levels of inhibition. We report here the use of the optimised Chou Talalay method to define synergistic antimalarial drug interactivity between emetine dihydrochloride hydrate and atovaquone. The novel findings present a potential route to harness the nanomolar antimalarial efficacy of this affordable natural product

A hierarchical kinetic theory of birth, death, and fission in age-structured interacting populations

We study mathematical models describing the evolution of stochastic age-structured populations. After reviewing existing approaches, we develop a complete kinetic framework for age-structured interacting populations undergoing birth, death and fission processes in spatially dependent environments. We define the full probability density for the population-size age chart and find results under specific conditions. Connections with more classical models are also explicitly derived. In particular, we show that factorial moments for non-interacting processes are described by a natural generalization of the McKendrick-von Foerster equation, which describes mean-field deterministic behavior. Our approach utilizes mixed-type, multidimensional probability distributions similar to those employed in the study of gas kinetics and with terms that satisfy BBGKY-like equation hierarchies

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions

The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment, utilizing the Matthews Correlation Coefficient (MCC) and Binding-site Distance Test (BDT) metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall’s τ, Spearman’s ρ and Pearson’s r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC) when Receiver Operator Characteristic (ROC) analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%), and one of the top manual groups (FN293) tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site prediction quality, in the absence of experimental data

Sharing Data for Public Health Research by Members of an International Online Diabetes Social Network

Background: Surveillance and response to diabetes may be accelerated through engaging online diabetes social networks (SNs) in consented research. We tested the willingness of an online diabetes community to share data for public health research by providing members with a privacy-preserving social networking software application for rapid temporal-geographic surveillance of glycemic control. Methods and Findings: SN-mediated collection of cross-sectional, member-reported data from an international online diabetes SN entered into a software applicaction we made available in a “Facebook-like” environment to enable reporting, charting and optional sharing of recent hemoglobin A1c values through a geographic display. Self-enrollment by 17% (n = 1,136) of n = 6,500 active members representing 32 countries and 50 US states. Data were current with 83.1% of most recent A1c values reported obtained within the past 90 days. Sharing was high with 81.4% of users permitting data donation to the community display. 34.1% of users also displayed their A1cs on their SN profile page. Users selecting the most permissive sharing options had a lower average A1c (6.8%) than users not sharing with the community (7.1%, p = .038). 95% of users permitted re-contact. Unadjusted aggregate A1c reported by US users closely resembled aggregate 2007–2008 NHANES estimates (respectively, 6.9% and 6.9%, p = 0.85). Conclusions: Success within an early adopter community demonstrates that online SNs may comprise efficient platforms for bidirectional communication with and data acquisition from disease populations. Advancing this model for cohort and translational science and for use as a complementary surveillance approach will require understanding of inherent selection and publication (sharing) biases in the data and a technology model that supports autonomy, anonymity and privacy.Centers for Disease Control and Prevention (U.S.) (P01HK000088-01)Centers for Disease Control and Prevention (U.S.) (P01HK000016 )National Institute of Alcohol Abuse and Alcoholism (U.S.) (R21 AA016638-01A1)National Center for Research Resources (U.S.) (1U54RR025224-01)Children's Hospital (Boston, Mass.) (Program for Patient Safety and Quality

Role of mitochondrial raft-like microdomains in the regulation of cell apoptosis

Lipid rafts are envisaged as lateral assemblies of specific lipids and proteins that dissociate and associate rapidly and form functional clusters in cell membranes. These structural platforms are not confined to the plasma membrane; indeed lipid microdomains are similarly formed at subcellular organelles, which include endoplasmic reticulum, Golgi and mitochondria, named raft-like microdomains. In addition, some components of raft-like microdomains are present within ER-mitochondria associated membranes. This review is focused on the role of mitochondrial raft-like microdomains in the regulation of cell apoptosis, since these microdomains may represent preferential sites where key reactions take place, regulating mitochondria hyperpolarization, fission-associated changes, megapore formation and release of apoptogenic factors. These structural platforms appear to modulate cytoplasmic pathways switching cell fate towards cell survival or death. Main insights on this issue derive from some pathological conditions in which alterations of microdomains structure or function can lead to severe alterations of cell activity and life span. In the light of the role played by raft-like microdomains to integrate apoptotic signals and in regulating mitochondrial dynamics, it is conceivable that these membrane structures may play a role in the mitochondrial alterations observed in some of the most common human neurodegenerative diseases, such as Amyotrophic lateral sclerosis, Huntington's chorea and prion-related diseases. These findings introduce an additional task for identifying new molecular target(s) of pharmacological agents in these pathologies

Design, fabrication and control of soft robots

Conventionally, engineers have employed rigid materials to fabricate precise, predictable robotic systems, which are easily modelled as rigid members connected at discrete joints. Natural systems, however, often match or exceed the performance of robotic systems with deformable bodies. Cephalopods, for example, achieve amazing feats of manipulation and locomotion without a skeleton; even vertebrates such as humans achieve dynamic gaits by storing elastic energy in their compliant bones and soft tissues. Inspired by nature, engineers have begun to explore the design and control of soft-bodied robots composed of compliant materials. This Review discusses recent developments in the emerging field of soft robotics.National Science Foundation (U.S.) (Grant IIS-1226883

MicroRNA profiling of cisplatinresistant oral squamous cell carcinoma cell lines enriched withcancer-stem-cell-like and epithelial-mesenchymal transition-type features

Oral cancer is of major public health problem in India. Current investigation was aimed to identify the specific deregulated miRNAs which are responsible for development of resistance phenotype through regulating their resistance related target gene expression in oral squamous cell carcinoma (OSCC). Cisplatin-resistant OSCC cell lines were developed from their parental human OSCC cell lines and subsequently characterised. The resistant cells exhibited enhanced proliferative, clonogenic capacity with significant up-regulation of P-glycoprotein (ABCB1), c-Myc, survivin, β-catenin and a putative cancer-stem-like signature with increased expression of CD44, whereas the loss of E-cadherin signifies induced EMT phenotype. A comparative analysis of miRNA expression profiling in parental and cisplatin-resistant OSCC cell lines for a selected sets (deregulated miRNAs in head and neck cancer) revealed resistance specific signature. Moreover, we observed similar expression pattern for these resistance specific signature miRNAs in neoadjuvant chemotherapy treated and recurrent tumours compared to those with newly diagnosed primary tumours in patients with OSCC. All these results revealed that these miRNAs play an important role in the development of cisplatin-resistance mainly through modulating cancer stem-cell-like and EMT-type properties in OSCC

Identifying chondroprotective diet-derived bioactives and investigating their synergism

Osteoarthritis (OA) is a multifactorial disease and nutrition is a modifiable factor that may contribute to disease onset or progression. A detailed understanding of mechanisms through which diet-derived bioactive molecules function and interact in OA is needed. We profiled 96 diet-derived, mainly plant-based bioactives using an in vitro model in chondrocytes, selecting four candidates for further study. We aimed to determine synergistic interactions between bioactives that affected the expression of key genes in OA. Selected bioactives, sulforaphane, apigenin, isoliquiritigenin and luteolin, inhibited one or more interleukin-1-induced metalloproteinases implicated in OA (MMP1, MMP13, ADAMTS4, ADAMTS5). Isoliquiritigenin and luteolin showed reactive oxygen species scavenging activity in chondrocytes whereas sulforaphane had no effect and apigenin showed only a weak trend. Sulforaphane inhibited the IL-1/NFκB and Wnt3a/TCF/Lef pathways and increased TGFβ/Smad2/3 and BMP6/Smad1/5/8 signalling. Apigenin showed potent inhibition of the IL-1/NFκB and TGFβ/Smad2/3 pathways, whereas luteolin showed only weak inhibition of the IL-1/NFκB pathway. All four bioactives inhibited cytokine-induced aggrecan loss from cartilage tissue explants. The combination of sulforaphane and isoliquiritigenin was synergistic for inhibiting MMP13 gene expression in chondrocytes. We conclude that dietary-derived bioactives may be important modulators of cartilage homeostasis and synergistic relationships between bioactives may have an anti-inflammatory and chondroprotective role

“Medically unexplained” symptoms and symptom disorders in primary care: prognosis-based recognition and classification

Background: Many patients consult their GP because they experience bodily symptoms. In a substantial proportion of cases, the clinical picture does not meet the existing diagnostic criteria for diseases or disorders. This may be because symptoms are recent and evolving or because symptoms are persistent but, either by their character or the negative results of clinical investigation cannot be attributed to disease: so-called “medically unexplained symptoms” (MUS). MUS are inconsistently recognised, diagnosed and managed in primary care. The specialist classification systems for MUS pose several problems in a primary care setting. The systems generally require great certainty about presence or absence of physical disease, they tend to be mind-body dualistic, and they view symptoms from a narrow specialty determined perspective. We need a new classification of MUS in primary care; a classification that better supports clinical decision-making, creates clearer communication and provides scientific underpinning of research to ensure effective interventions. Discussion: We propose a classification of symptoms that places greater emphasis on prognostic factors. Prognosis-based classification aims to categorise the patient’s risk of ongoing symptoms, complications, increased healthcare use or disability because of the symptoms. Current evidence suggests several factors which may be used: symptom characteristics such as: number, multi-system pattern, frequency, severity. Other factors are: concurrent mental disorders, psychological features and demographic data. We discuss how these characteristics may be used to classify symptoms into three groups: self-limiting symptoms, recurrent and persistent symptoms, and symptom disorders. The middle group is especially relevant in primary care; as these patients generally have reduced quality of life but often go unrecognised and are at risk of iatrogenic harm. The presented characteristics do not contain immediately obvious cut-points, and the assessment of prognosis depends on a combination of several factors. Conclusion: Three criteria (multiple symptoms, multiple systems, multiple times) may support the classification into good, intermediate and poor prognosis when dealing with symptoms in primary care. The proposed new classification specifically targets the patient population in primary care and may provide a rational framework for decision-making in clinical practice and for epidemiologic and clinical research of symptoms