Slc15a4, a gene required for pDC sensing of TLR ligands, is required to control persistent viral infection

Plasmacytoid dendritic cells (pDCs) are the major producers of type I IFN in response to viral infection and have been shown to direct both innate and adaptive immune responses in vitro. However, in vivo evidence for their role in viral infection is lacking. We evaluated the contribution of pDCs to acute and chronic virus infection using the feeble mouse model of pDC functional deficiency. We have previously demonstrated that feeble mice have a defect in TLR ligand sensing. Although pDCs were found to influence early cytokine secretion, they were not required for control of viremia in the acute phase of the infection. However, T cell priming was deficient in the absence of functional pDCs and the virus-specific immune response was hampered. Ultimately, infection persisted in feeble mice. We conclude that pDCs are likely required for efficient T cell priming and subsequent viral clearance. Our data suggest that reduced pDC functionality may lead to chronic infection.

IFPA Meeting 2011 workshop report I: Placenta: Predicting future health; roles of lipids in the growth and development of feto-placental unit; placental nutrient sensing; placental research to solve clinical problems--a translational approach

Workshops are an important part of the IFPA annual meeting as they allow for discussion of specialized topics. At IFPA meeting 2011 there were twelve themed workshops, four of which are summarized in this report. These workshops related to both basic science and clinical research into placental growth and nutrient sensing and were divided into 1) placenta: predicting future health; 2) roles of lipids in the growth and development of feto-placental unit; 3) placental nutrient sensing; 4) placental research to solve clinical problems: a translational approach.

Microwave remote sensing of stratospheric trace gases using digital Fast Fourier Transform spectrometers

The Institute of Applied Physics observes middle atmospheric trace gases, such as ozone and water vapour, by microwave radiometry. We report on the comparison of measurements using a novel digital Fast Fourier Transform and accousto optical spectrometers. First tests made on ground are presented as well as first experience about the use of such spectrometers under aircraft conditions.

Ligament balancing in TKA: Evaluation of a force-sensing device and the influence of patellar eversion and ligament release

Ligament balancing in total knee arthroplasty may have an important influence on joint stability and prosthesis lifetime. In order to provide quantitative information and assistance during ligament balancing, a device that intraoperatively measures knee joint forces and moments was developed. Its performance and surgical advantages were evaluated on six cadaver specimens mounted on a knee joint loading apparatus allowing unconstrained knee motion as well as compression and varus-valgus loading. Four different experiments were performed on each specimen. (1) Knee joints were axially loaded. Comparison between applied and measured compressive forces demonstrated the accuracy and reliability of in situ measurements (1.8N). (2) Assessment of knee stability based on condyle contact forces or varus-valgus moments were compared to the current surgical method (difference of varus-valgus loads causing condyle lift-off). The force-based approach was equivalent to the surgical method while the moment-based, which is considered optimal, showed a tendency of lateral imbalance. (3) To estimate the importance of keeping the patella in its anatomical position during imbalance assessment, the effect of patellar eversion on the mediolateral distribution of tibiofemoral contact forces was measured. One fourth of the contact force induced by the patellar load was shifted to the lateral compartment. (4) The effect of minor and major medial collateral ligament releases was biomechanically quantified. On average, the medial contact force was reduced by 20% and 46%, respectively. Large variation among specimens reflected the difficulty of ligament release and the need for intraoperative force monitoring. This series of experiments thus demonstrated the device's potential to improve ligament balancing and survivorship of total knee arthroplasty.

Estimation of the degree of polarization through computational sensing

The degree of polarization of a refected field from active laser illumination can be used for object identifcation and classifcation. The goal of this study is to investigate methods for estimating the degree of polarization for refected fields with active laser illumination, which involves the measurement and processing of two orthogonal field components (complex amplitudes), two orthogonal intensity components, and the total field intensity. We propose to replace interferometric optical apparatuses with a computational approach for estimating the degree of polarization from two orthogonal intensity data and total intensity data. Cramer-Rao bounds for each of the three sensing modalities with various noise models are computed. Algebraic estimators and maximum-likelihood (ML) estimators are proposed. Active-set algorithm and expectation-maximization (EM) algorithm are used to compute ML estimates. The performances of the estimators are compared with each other and with their corresponding Cramer-Rao bounds. Estimators for four-channel polarimeter (intensity interferometer) sensing have a better performance than orthogonal intensities estimators and total intensity estimators. Processing the four intensities data from polarimeter, however, requires complicated optical devices, alignment, and four CCD detectors. It only requires one or two detectors and a computer to process orthogonal intensities data and total intensity data, and the bounds and estimator performances demonstrate that reasonable estimates may still be obtained from orthogonal intensities or total intensity data. Computational sensing is a promising way to estimate the degree of polarization.

Comparing remote sensing and ground-based methods of quantifying cover type and carbon storage in an urban forest

Understanding the canopy cover of an urban environment leads to better estimates of carbon storage and more informed management decisions by urban foresters. The most commonly used method for assessing urban forest cover type extent is ground surveys, which can be both timeconsuming and expensive. The analysis of aerial photos is an alternative method that is faster, cheaper, and can cover a larger number of sites, but may be less accurate. The objectives of this paper were (1) to compare three methods of cover type assessment for Los Angeles, CA: handdelineation of aerial photos in ArcMap, supervised classification of aerial photos in ERDAS Imagine, and ground-collected data using the Urban Forest Effects (UFORE) model protocol; (2) to determine how well remote sensing methods estimate carbon storage as predicted by the UFORE model; and (3) to explore the influence of tree diameter and tree density on carbon storage estimates. Four major cover types (bare ground, fine vegetation, coarse vegetation, and impervious surfaces) were determined from 348 plots (0.039 ha each) randomly stratified according to land-use. Hand-delineation was better than supervised classification at predicting ground-based measurements of cover type and UFORE model-predicted carbon storage. Most error in supervised classification resulted from shadow, which was interpreted as unknown cover type. Neither tree diameter or tree density per plot significantly affected the relationship between carbon storage and canopy cover. The efficiency of remote sensing rather than in situ data collection allows urban forest managers the ability to quickly assess a city and plan accordingly while also preserving their often-limited budget.