Breeding for Quantitative Resistance to Leaf Blights of Corn: A Continuing Success Story

The development of high yielding, disease resistant hybrids is the goal of most public and private corn breeding programs. These programs have largely been successful in reducing the incidence and severity of foliar diseases of corn in the U.S. Significant, damaging levels of leaf diseases are considered the exception throughout most of the corn belt, and a healthy corn crop the norm. This highly desirable situation did not arise by chance or good fortune, but rather is the result of dedicated efforts of corn breeders and pathologists over the decades. Unlike most other crops, corn breeders have been able to successfully integrate quantitative resistance into their elite germplasm and select for it during the breeding process. Single, race-specific genes have been used in corn to a limited extent, but their use has largely been abandoned due to the well documented ability of pathogens to overcome this type of resistance and the conservative nature of the backcross breeding methods used to incorporate these genes into elite lines

Random selection of citizens for technological decision making

Random selection provides a way to overcome some of the usual problems of citizen participation in technological decision making. It offers representativeness with a minimum of bias and susceptibility to vested interests. There are a number of requirements for the effectiveness of the random selection approach, such as that citizens are interested and capable of rational deliberation. A number of recent experiments with policy juries and planning cells are assessed to see how well they satisfy the requirements for the effectiveness of the approach. While random selection shows great promise as a means for involving citizens in technological decision making, there are obstacles to promoting the use of this approach for policy purposes, perhaps especially because it so effectively circumscribes the role of political elites

Photoactivatable genetically encoded calcium indicators for targeted neuronal imaging.

Circuit mapping requires knowledge of both structural and functional connectivity between cells. Although optical tools have been made to assess either the morphology and projections of neurons or their activity and functional connections, few probes integrate this information. We have generated a family of photoactivatable genetically encoded Ca(2+) indicators that combines attributes of high-contrast photolabeling with high-sensitivity Ca(2+) detection in a single-color protein sensor. We demonstrated in cultured neurons and in fruit fly and zebrafish larvae how single cells could be selected out of dense populations for visualization of morphology and high signal-to-noise measurements of activity, synaptic transmission and connectivity. Our design strategy is transferrable to other sensors based on circularly permutated GFP (cpGFP)

Probing sporadic and familial Alzheimer's disease using induced pluripotent stem cells.

Our understanding of Alzheimer's disease pathogenesis is currently limited by difficulties in obtaining live neurons from patients and the inability to model the sporadic form of the disease. It may be possible to overcome these challenges by reprogramming primary cells from patients into induced pluripotent stem cells (iPSCs). Here we reprogrammed primary fibroblasts from two patients with familial Alzheimer's disease, both caused by a duplication of the amyloid-β precursor protein gene (APP; termed APP(Dp)), two with sporadic Alzheimer's disease (termed sAD1, sAD2) and two non-demented control individuals into iPSC lines. Neurons from differentiated cultures were purified with fluorescence-activated cell sorting and characterized. Purified cultures contained more than 90% neurons, clustered with fetal brain messenger RNA samples by microarray criteria, and could form functional synaptic contacts. Virtually all cells exhibited normal electrophysiological activity. Relative to controls, iPSC-derived, purified neurons from the two APP(Dp) patients and patient sAD2 exhibited significantly higher levels of the pathological markers amyloid-β(1-40), phospho-tau(Thr 231) and active glycogen synthase kinase-3β (aGSK-3β). Neurons from APP(Dp) and sAD2 patients also accumulated large RAB5-positive early endosomes compared to controls. Treatment of purified neurons with β-secretase inhibitors, but not γ-secretase inhibitors, caused significant reductions in phospho-Tau(Thr 231) and aGSK-3β levels. These results suggest a direct relationship between APP proteolytic processing, but not amyloid-β, in GSK-3β activation and tau phosphorylation in human neurons. Additionally, we observed that neurons with the genome of one sAD patient exhibited the phenotypes seen in familial Alzheimer's disease samples. More generally, we demonstrate that iPSC technology can be used to observe phenotypes relevant to Alzheimer's disease, even though it can take decades for overt disease to manifest in patients

Interfacing and Verifying ALHAT Safe Precision Landing Systems with the Morpheus Vehicle

The NASA Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) project developed a suite of prototype sensors to enable autonomous and safe precision landing of robotic or crewed vehicles under any terrain lighting conditions. Development of the ALHAT sensor suite was a cross-NASA effort, culminating in integration and testing on-board a variety of terrestrial vehicles toward infusion into future spaceflight applications. Terrestrial tests were conducted on specialized test gantries, moving trucks, helicopter flights, and a flight test onboard the NASA Morpheus free-flying, rocket-propulsive flight-test vehicle. To accomplish these tests, a tedious integration process was developed and followed, which included both command and telemetry interfacing, as well as sensor alignment and calibration verification to ensure valid test data to analyze ALHAT and Guidance, Navigation and Control (GNC) performance. This was especially true for the flight test campaign of ALHAT onboard Morpheus. For interfacing of ALHAT sensors to the Morpheus flight system, an adaptable command and telemetry architecture was developed to allow for the evolution of per-sensor Interface Control Design/Documents (ICDs). Additionally, individual-sensor and on-vehicle verification testing was developed to ensure functional operation of the ALHAT sensors onboard the vehicle, as well as precision-measurement validity for each ALHAT sensor when integrated within the Morpheus GNC system. This paper provides some insight into the interface development and the integrated-systems verification that were a part of the build-up toward success of the ALHAT and Morpheus flight test campaigns in 2014. These campaigns provided valuable performance data that is refining the path toward spaceflight infusion of the ALHAT sensor suite

Algorithms for optimizing drug therapy

BACKGROUND: Drug therapy has become increasingly efficient, with more drugs available for treatment of an ever-growing number of conditions. Yet, drug use is reported to be sub optimal in several aspects, such as dosage, patient's adherence and outcome of therapy. The aim of the current study was to investigate the possibility to optimize drug therapy using computer programs, available on the Internet. METHODS: One hundred and ten officially endorsed text documents, published between 1996 and 2004, containing guidelines for drug therapy in 246 disorders, were analyzed with regard to information about patient-, disease- and drug-related factors and relationships between these factors. This information was used to construct algorithms for identifying optimum treatment in each of the studied disorders. These algorithms were categorized in order to define as few models as possible that still could accommodate the identified factors and the relationships between them. The resulting program prototypes were implemented in HTML (user interface) and JavaScript (program logic). RESULTS: Three types of algorithms were sufficient for the intended purpose. The simplest type is a list of factors, each of which implies that the particular patient should or should not receive treatment. This is adequate in situations where only one treatment exists. The second type, a more elaborate model, is required when treatment can by provided using drugs from different pharmacological classes and the selection of drug class is dependent on patient characteristics. An easily implemented set of if-then statements was able to manage the identified information in such instances. The third type was needed in the few situations where the selection and dosage of drugs were depending on the degree to which one or more patient-specific factors were present. In these cases the implementation of an established decision model based on fuzzy sets was required. Computer programs based on one of these three models could be constructed regarding all but one of the studied disorders. The single exception was depression, where reliable relationships between patient characteristics, drug classes and outcome of therapy remain to be defined. CONCLUSION: Algorithms for optimizing drug therapy can, with presumably rare exceptions, be developed for any disorder, using standard Internet programming methods

Imaging of a Transitional Disk Gap in Reflected Light: Indications of Planet Formation Around the Young Solar Analog LkCa 15

We present H- and Ks-band imaging data resolving the gap in the transitional disk around LkCa 15, revealing the surrounding nebulosity. We detect sharp elliptical contours delimiting the nebulosity on the inside as well as the outside, consistent with the shape, size, ellipticity, and orientation of starlight reflected from the far-side disk wall, whereas the near-side wall is shielded from view by the disk's optically thick bulk. We note that forward-scattering of starlight on the near-side disk surface could provide an alternate interpretation of the nebulosity. In either case, this discovery provides confirmation of the disk geometry that has been proposed to explain the spectral energy distributions (SED) of such systems, comprising an optically thick outer disk with an inner truncation radius of ~46 AU enclosing a largely evacuated gap. Our data show an offset of the nebulosity contours along the major axis, likely corresponding to a physical pericenter offset of the disk gap. This reinforces the leading theory that dynamical clearing by at least one orbiting body is the cause of the gap. Based on evolutionary models, our high-contrast imagery imposes an upper limit of 21 Jupiter masses on companions at separations outside of 0.1" and of 13 Jupiter masses outside of 0.2". Thus, we find that a planetary system around LkCa 15 is the most likely explanation for the disk architecture.Comment: 5 pages, 4 figures, accepted for publication in ApJ Letters. Minor change to Figure