PbSR is synthesized in macrogametocytes and involved in formation of the malaria crystalloids

Crystalloids are transient organelles that form in developing malaria ookinetes and disappear after ookinete-to-oocyst transition. Their origins and functions remain poorly understood. The Plasmodium berghei scavenger receptor-like protein PbSR is essential for mosquito-to-host transmission of the parasite: PbSR knockout parasites produce normal numbers of oocysts that fail to form sporozoites, pointing to a role for PbSR in the oocyst during sporogony. Here, using fluorescent protein tagging and targeted gene disruption, we show that PbSR is synthesized in macrogametocytes, gets targeted to the crystalloids of developing ookinetes and is involved in crystalloid formation. While oocyst sporulation rates of PbSR knockout parasites are highly reduced in parasite-infected mosquitoes, sporulation rates in vitro are not adversely affected, supporting the view that mosquito factors could be involved in the PbSR loss-of-function phenotype. These findings are the first to identify a parasite protein involved with the crystalloid organelle, and suggest a novel protein-trafficking mechanism to deliver PbSR to the oocysts

Fiber Loop Ringdown — a Time-Domain Sensing Technique for Multi-Function Fiber Optic Sensor Platforms: Current Status and Design Perspectives

Fiber loop ringdown (FLRD) utilizes an inexpensive telecommunications light source, a photodiode, and a section of single-mode fiber to form a uniform fiber optic sensor platform for sensing various quantities, such as pressure, temperature, strain, refractive index, chemical species, biological cells, and small volume of fluids. In FLRD, optical losses of a light pulse in a fiber loop induced by changes in a quantity are measured by the light decay time constants. FLRD measures time to detect a quantity; thus, FLRD is referred to as a time-domain sensing technique. FLRD sensors have near real-time response, multi-pass enhanced high-sensitivity, and relatively low cost (i.e., without using an optical spectral analyzer). During the last eight years since the introduction of the original form of fiber ringdown spectroscopy, there has been increasing interest in the FLRD technique in fiber optic sensor developments, and new application potential is being explored. This paper first discusses the challenging issues in development of multi-function, fiber optic sensors or sensor networks using current fiber optic sensor sensing schemes, and then gives a review on current fiber optic sensor development using FLRD technique. Finally, design perspectives on new generation, multi-function, fiber optic sensor platforms using FLRD technique are particularly presented

MOFIA: A chemoinformatic webserver for the prediction of CO<inf>2</inf> adsorption in Metal Organic Frameworks (MOF)

Nanoporous metal-organic framework (MOF) materials are strong candidates for energy efficient carbon capture and storage (CCS) technologies. A total of ∼20,000 hypothetical MOFs were ab initio screened for CO2 adsorption using grand canonical Monte-Carlo (GCMC) simulations. Novel radial distribution function (RDF) scores were modified for periodic systems to predict the CO2 adsorption of MOFs using chemoinformatic models. The test set predictions yielded accuracies of 0.76 and 0.85 at 0.1 bar and 1 bar, respectively. The models were used to screen a large database for high performing MOFs and the top 100 structures were successfully validated by GCMC simulations. The chemoinformatic predictors of the CO2 adsorption of MOFs are available online at http://titan.chem.uottawa.ca/woolab/MOFIA/ #carbondioxide. © 2013 Materials Research Society

Atomic Property Weighted Radial Distribution Functions Descriptors of Metal–Organic Frameworks for the Prediction of Gas Uptake Capacity

Metal–organic frameworks (MOFs) are porous materials with exceptional host–guest properties with huge potential for gas separation. The combinatorial design of MOFs demands the <i>in silico</i> screening of the nearly infinite combinations of structural building blocks using efficient computational tools. We report here a novel atomic property weighted radial distribution function (AP-RDF) descriptor tailored for large-scale Quantitative Structure–Property Relationship (QSPR) predictions of gas adsorption of MOFs. A total of ∼58,000 hypothetical MOF structures were used to calibrate correlation models of the methane, N₂, and CO₂ uptake capacities from grand-canonical Monte Carlo (GCMC) simulations. The principal component analysis (PCA) transform of the AP-RDF descriptors exhibited good discrimination of MOF inorganic SBUs, geometrical properties, and more surprisingly gas uptake capacities. While the simulated uptake capacities correlated poorly to the void fraction, surface area, and pore size, the newly introduced AP-RDF scores yielded outstanding QSPR predictions for an external test set of ∼25,000 MOFs with <i>R</i>^<i>2</i> values in the range from 0.70 to 0.82. The accuracy of the predictions decreased at low pressures, mainly for MOFs with V₂O₂ or Zr₆O₈ inorganic structural building units (SBUs) and organic SBUs with fluorine substituents. The QSPR models can serve as efficient filtering tools to detecting promising high-performing candidates at the early stage of virtual high-throughput screening of novel porous materials. The predictive models of the gas uptake capacities of MOFs are available online via our MOF informatics analysis (MOFIA) tool

Integrated Approaches to Testing and Assessment Under Canada's Chemicals Management Plan: Proposed Phenols Case Study for Review Cycle #3

Presentation on IATA case study for phenols which is joint project with Health Canada and NCCT, presented at the OECD IATA Case Study Meeting No. 2 in Paris, France November 201