Trigger release liposome systems:local and remote controlled delivery?

Target-specific delivery has become an integral area of research in order to increase bioavailability and reduce the toxic effects of drugs. As a drug-delivery option, trigger-release liposomes offer sophisticated targeting and greater control-release capabilities. These are broadly divided into two categories; those that utilise the local environment of the target site where there may be an upregulation in certain enzymes or a change in pH and those liposomes that are triggered by an external physical stimulus such as heat, ultrasound or light. These release mechanisms offer a greater degree of control over when and where the drug is released; furthermore, targeting of diseased tissue is enhanced by incorporation of target-specific components such as antibodies. This review aims to show the development of such trigger release liposome systems and the current research in this field.

Event trigger identification for biomedical events extraction using domain knowledge

Motivation: In molecular biology, molecular events describe observable alterations of biomolecules, such as binding of proteins or RNA production. These events might be responsible for drug reactions or development of certain diseases. As such, biomedical event extraction, the process of automatically detecting description of molecular interactions in research articles, attracted substantial research interest recently. Event trigger identification, detecting the words describing the event types, is a crucial and prerequisite step in the pipeline process of biomedical event extraction. Taking the event types as classes, event trigger identification can be viewed as a classification task. For each word in a sentence, a trained classifier predicts whether the word corresponds to an event type and which event type based on the context features. Therefore, a well-designed feature set with a good level of discrimination and generalization is crucial for the performance of event trigger identification. Results: In this article, we propose a novel framework for event trigger identification. In particular, we learn biomedical domain knowledge from a large text corpus built from Medline and embed it into word features using neural language modeling. The embedded features are then combined with the syntactic and semantic context features using the multiple kernel learning method. The combined feature set is used for training the event trigger classifier. Experimental results on the golden standard corpus show that >2.5% improvement on F-score is achieved by the proposed framework when compared with the state-of-the-art approach, demonstrating the effectiveness of the proposed framework. © 2014 The Author 2014. The source code for the proposed framework is freely available and can be downloaded at http://cse.seu.edu.cn/people/zhoudeyu/ETI_Sourcecode.zip.

Fluorescent probe for detection of bacteria:conformational trigger upon bacterial reduction of an azo bridge

Using biomimetic chemical reduction or Clostridium perfringens cell extract containing azoreductase, the dimer-fluorescent probe 2,4-O-bisdansyl-6,7- diazabicyclooct-6-ene, which possesses a conformationally constrained cis-azo bridge, is reduced to the tetra-equatorial 2,4-O-bisdansyl-cyclohexyl-3,5- bisammonium salt which exhibits fluorescence indicative of a dansyl monomer. © 2012 The Royal Society of Chemistry.

Influencing online grocery innovation:anti-choice as a trigger for activity fragmentation and multi-tasking

This paper reveals how activity fragmentation and multi-tasking become tools of consumer anti-choice in the online grocery sector: facilitated by new technology practices that positively encourage anti-choice. This is demonstrated through five long-term ethnographic case studies of households in the Portsmouth area of England. All the respondents made some form of conscious effort to minimize the amount of time they spent in ‘big box’ grocery stores. They spend more time at home in planning, searching, socializing online, cumulating and fulfilling internet orders than if they had visited a store: something that all could easily do. The findings suggest the need for constant innovation by internet grocers if they are to remain in tune with dynamic consumer lifestyles and advances in technology. Examples of upcoming technologies requiring retailers to re-think their internet strategies are discussed in view of the possibilities offered by activity fragmentation and multi-tasking.

Rib-cage-movement measurements as a potential new trigger signal in non-invasive mechanical ventilation

Non-invasive ventilation performed through an oronasal mask is a standard in clinical and homecare mechanical ventilation. Besides all its advantages, inevitable leaks through the mask cause errors in the feedback information provided by the airflow sensor and, hence, patient-ventilator asynchrony with multiple negative consequences. Here we investigate a new way to provide a trigger to the ventilator. The method is based on the measurement of rib cage movement at the onset of inspiration and during breathing by fibre-optic sensors. In a series of simultaneous measurements by a long-period fibre grating sensor and pneumotachograph we provide the statistical evidence of the 200 ms lag of the pneumo with respect the fibre-optic signal. The lag is registered consistently across three independent delay metrics. Further, we discuss exceptions from this trend and identify the needed improvements to the proposed fibre-sensing scheme.

The extracellular surface of the GLP-1 receptor is a molecular trigger for biased agonism

Ligand-directed signal bias offers opportunities for sculpting molecular events, with the promise of better, safer therapeutics. Critical to the exploitation of signal bias is an understanding of the molecular events coupling ligand binding to intracellular signaling. Activation of class B G protein-coupled receptors is driven by interaction of the peptide N terminus with the receptor core. To understand how this drives signaling, we have used advanced analytical methods that enable separation of effects on pathway-specific signaling from those that modify agonist affinity and mapped the functional consequence of receptor modification onto three-dimensional models of a receptor-ligand complex. This yields molecular insights into the initiation of receptor activation and the mechanistic basis for biased agonism. Our data reveal that peptide agonists can engage different elements of the receptor extracellular face to achieve effector coupling and biased signaling providing a foundation for rational design of biased agonists.