HABIT FORMATION AND DEMAND SYSTEM ESTIMATES FOR FLUID MILK IN SPAIN

Demand and Price Analysis, Livestock Production/Industries,

Impact of tumor-specific targeting on the biodistribution and efficacy of siRNA nanoparticles measured by multimodality in vivo imaging

Targeted delivery represents a promising approach for the development of safer and more effective therapeutics for oncology applications. Although macromolecules accumulate nonspecifically in tumors through the enhanced permeability and retention (EPR) effect, previous studies using nanoparticles to deliver chemotherapeutics or siRNA demonstrated that attachment of cell-specific targeting ligands to the surface of nanoparticles leads to enhanced potency relative to nontargeted formulations. Here, we use positron emission tomography (PET) and bioluminescent imaging to quantify the in vivo biodistribution and function of nanoparticles formed with cyclodextrin-containing polycations and siRNA. Conjugation of 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid to the 5' end of the siRNA molecules allows labeling with 64Cu for PET imaging. Bioluminescent imaging of mice bearing luciferase-expressing Neuro2A s.c. tumors before and after PET imaging enables correlation of functional efficacy with biodistribution data. Although both nontargeted and transferrin-targeted siRNA nanoparticles exhibit similar biodistribution and tumor localization by PET, transferrin-targeted siRNA nanoparticles reduce tumor luciferase activity by {approx}50% relative to nontargeted siRNA nanoparticles 1 d after injection. Compartmental modeling is used to show that the primary advantage of targeted nanoparticles is associated with processes involved in cellular uptake in tumor cells rather than overall tumor localization. Optimization of internalization may therefore be key for the development of effective nanoparticle-based targeted therapeutics

A role for TASK-1 (KCNK3) channels in the chemosensory control of breathing

Acid-sensitive K+ channels of the tandem P-domain K+-channel family (TASK-1 and TASK-3) have been implicated in peripheral and central respiratory chemosensitivity; however, because of the lack of decisive pharmacological agents, the final proof of the role of the TASK channel in the chemosensory control of breathing has been missing. In the mouse, TASK-1 and TASK-3 channels are dispensable for central respiratory chemosensitivity (Mulkey et al., 2007Go). Here, we have used knock-out animals to determine whether TASK-1 and TASK-3 channels play a role in the carotid body function and chemosensory control of breathing exerted by the carotid body chemoreceptors. Ventilatory responses to hypoxia (10% O2 in inspired air) and moderate normoxic hypercapnia (3–6% CO2 in inspired air) were significantly reduced in TASK-1 knock-out mice. In contrast, TASK-3-deficient mice showed responses to both stimuli that were similar to those developed by their wild-type counterparts. TASK-1 channel deficiency resulted in a marked reduction of the hypoxia (by 49%)- and CO2 (by 68%)-evoked increases in the carotid sinus nerve chemoafferent discharge recorded in the in vitro superfused carotid body/carotid sinus nerve preparations. Deficiency in both TASK-1 and TASK-3 channels increased baseline chemoafferent activity but did not cause a further reduction of the carotid body chemosensory responses. These observations provide direct evidence that TASK-1 channels contribute significantly to the increases in the carotid body chemoafferent discharge in response to a decrease in arterial PO2 or an increase in PCO2/[H+]. TASK-1 channels therefore play a key role in the control of ventilation by peripheral chemoreceptors

Orange-Flesh Sweet Potato - Promising Partnerships for Assuring the Integration of Nutritional Concerns into Agricultural Research and Extension

Research Results from the Department of Policy Analysis MARD-Directorate of Economicsfood security, food policy, Mozambique, sweet potato, malnutrition, Crop Production/Industries, Food Security and Poverty, Q18,

Finding Function in Form: Compositional Character Models for Open Vocabulary Word Representation

We introduce a model for constructing vector representations of words by composing characters using bidirectional LSTMs. Relative to traditional word representation models that have independent vectors for each word type, our model requires only a single vector per character type and a fixed set of parameters for the compositional model. Despite the compactness of this model and, more importantly, the arbitrary nature of the form-function relationship in language, our "composed" word representations yield state-of-the-art results in language modeling and part-of-speech tagging. Benefits over traditional baselines are particularly pronounced in morphologically rich languages (e.g., Turkish)