CHEMICAL ENGINEERING DIVISION BURNUP, CROSS SECTIONS, AND DOSIMETRY SEMIANNUAL REPORT, JANUARY--JUNE 1972.

Research and development efforts of the burnup, cross sections and dosimetry programs in the Chemical Engineering Division of Argonne National Laboratory are reported for the period January to June 1972. Work is reported in the following areas: (1) development of an X-ray spectrometric method for the determination of the rare-earth fission products and application of this method to the determinations of burnup in nuclear fuels; (2) determination of fast ·fission yields of bum up monitors and other fission products; (3) a search for a spon~aneously fissioning isomer of {sup 241}Pu; (4) measurements of the tritium and alpha particle yields in fast-neutron fission of {sup 235}U and {sup 239}Pu; (5) evaluations of available data on the differential cross sections for the {sup 56}Fe(n,p){sup 56}Mn and {sup 32}S(n,p){sup 32}P reactions; and (6) measurements of both fission rates by solid-state track recorders and reaction rates by foil activation, in the Coupled Fast Reactivity Measurement Facility

Deep Learning-Based Psoriasis Assessment: Harnessing Clinical Trial Imaging for Accurate Psoriasis Area Severity Index Prediction

Introduction: Image-based machine learning holds great promise for facilitating clinical care; however, the datasets often used for model training differ from the interventional clinical trial-based findings frequently used to inform treatment guidelines. Here, we draw on longitudinal imaging of psoriasis patients undergoing treatment in the Ultima 2 clinical trial (NCT02684357), including 2,700 body images with psoriasis area severity index (PASI) annotations by uniformly trained dermatologists. Methods: An image-processing workflow integrating clinical photos of multiple body regions into one model pipeline was developed, which we refer to as the “One-Step PASI” framework due to its simultaneous body detection, lesion detection, and lesion severity classification. Group-stratified cross-validation was performed with 145 deep convolutional neural network models combined in an ensemble learning architecture. Results: The highest-performing model demonstrated a mean absolute error of 3.3, Lin’s concordance correlation coefficient of 0.86, and Pearson correlation coefficient of 0.90 across a wide range of PASI scores comprising disease classifications of clear skin, mild, and moderate-to-severe disease. Within-person, time-series analysis of model performance demonstrated that PASI predictions closely tracked the trajectory of physician scores from severe to clear skin without systematically over- or underestimating PASI scores or percent changes from baseline. Conclusion: This study demonstrates the potential of image processing and deep learning to translate otherwise inaccessible clinical trial data into accurate, extensible machine learning models to assess therapeutic efficacy

Towards an integrated set of surface meteorological observations for climate science and applications

Observations are the foundation for understanding the climate system. Yet, currently available land meteorological data are highly fractured into various global, regional and national holdings for different variables and timescales, from a variety of sources, and in a mixture of formats. Added to this, many data are still inaccessible for analysis and usage. To meet modern scientific and societal demands as well as emerging needs such as the provision of climate services, it is essential that we improve the management and curation of available land-based meteorological holdings. We need a comprehensive global set of data holdings, of known provenance, that is truly integrated both across Essential Climate Variables (ECVs) and across timescales to meet the broad range of stakeholder needs. These holdings must be easily discoverable, made available in accessible formats, and backed up by multi-tiered user support. The present paper provides a high level overview, based upon broad community input, of the steps that are required to bring about this integration. The significant challenge is to find a sustained means to realize this vision. This requires a long-term international program. The database that results will transform our collective ability to provide societally relevant research, analysis and predictions in many weather and climate related application areas across much of the globe

Cancer stem cell drugs target K-ras signaling in a stemness context

Cancer stem cells (CSCs) are considered to be responsible for treatment relapse and have therefore become a major target in cancer research. Salinomycin is the most established CSC inhibitor. However, its primary mechanistic target is still unclear, impeding the discovery of compounds with similar anti-CSC activity. Here, we show that salinomycin very specifically interferes with the activity of K-ras4B, but not H-ras, by disrupting its nanoscale membrane organization. We found that caveolae negatively regulate the sensitivity to this drug. On the basis of this novel mechanistic insight, we defined a K-ras-associated and stem cell-derived gene expression signature that predicts the drug response of cancer cells to salinomycin. Consistent with therapy resistance of CSC, 8% of tumor samples in the TCGA-database displayed our signature and were associated with a significantly higher mortality. Using our K-ras-specific screening platform, we identified several new candidate CSC drugs. Two of these, ophiobolin A and conglobatin A, possessed a similar or higher potency than salinomycin. Finally, we established that the most potent compound, ophiobolin A, exerts its K-ras4B-specific activity through inactivation of calmodulin. Our data suggest that specific interference with the K-ras4B/calmodulin interaction selectively inhibits CSC.Peer reviewe

Quantitaton of rate of gastrointestinal and buccal absorption of acidic and basic drugs based on extraction theory

Equations have been derived which quantitatively describe the rate of gastrointestinal and buccal absorption of acidic and basic drugs as a function of pH of aqueous lumenal contents and time. The equations have been used to fit observed data in the literature, and the estimated parameters are reported. An equation which describes the renal clearance of an acidic or basic drug as a function of urinary pH is also derived. In essence, the equations quantitate the pH-partition hypothesis and explain most, if not all, related observed data in the literature. The results suggest that the aqueous diffusion layer may not rate-limit absorption of monomeric drug molecules but that absorption is rate-limited by transfer of drug out of the membrane in vivo.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45024/1/10928_2005_Article_BF01060026.pd

Fuel-performance-improvement program. Semiannual progress report, October 1980-March 1981. [Sphere-pac and annular-coated-pressurized]

Progress on the Fuel Performance Improvement Program's fuel test and demonstration irradiations is reported for the period of October 1980-March 1981. The purpose of the program is to test and demonstrate improved light water reactor fuel concepts that are more resistant to failure from pellet-cladding interaction during power increases than standard pellet fuel. This would also offer extended burnup potential and, hence, improved uranium utilization

Fuel performance improvement program. Semiannual progress report, April-September 1980

Progress on the Fuel Performance Improvement Program's fuel test and demonstration irradiations is reported for the period April-September, 1980. Included are results of out-of-reactor experiments with zircaloy cladding on the iodine assisted stress corrosion cracking mechanism. Preliminary results from the first eight ramp tests performed in the Halden Boiling Water Reactor are reported. The status of demonstration fuel irradiations in the Big Rock Point Reactor is described