Action languages: Dimensions, effects

Dimensions of action languages are discussed for communication between humans and machines, and the message handling capabilities of object oriented programming systems are examined. Design of action languages is seen to be very contextual. Economical and effective design will depend on features of situations, the tasks intended to be accomplished, and the nature of the devices themselves. Current object oriented systems turn out to have fairly simple and straightforward message handling facilities, which in themselves do little to buffer action or even in some cases to handle competing messages. Even so, it is possible to program a certain amount of discretion about how they react to messages. Such thoughtfulness and perhaps relative autonomy of program modules seems prerequisite to future systems to handle complex interactions in changing situations

Androgen receptor as a mediator and biomarker of radioresistance in triple-negative breast cancer.

Increased rates of locoregional recurrence have been observed in triple-negative breast cancer despite chemotherapy and radiation therapy. Thus, approaches that combine therapies for radiosensitization in triple-negative breast cancer are critically needed. We characterized the radiation therapy response of 21 breast cancer cell lines and paired this radiation response data with high-throughput drug screen data to identify androgen receptor as a top target for radiosensitization. Our radiosensitizer screen nominated bicalutamide as the drug most effective in treating radiation therapy-resistant breast cancer cell lines. We subsequently evaluated the expression of androgen receptor in >2100 human breast tumor samples and 51 breast cancer cell lines and found significant heterogeneity in androgen receptor expression with enrichment at the protein and RNA level in triple-negative breast cancer. There was a strong correlation between androgen receptor RNA and protein expression across all breast cancer subtypes (R2 = 0.72, p < 0.01). In patients with triple-negative breast cancer, expression of androgen receptor above the median was associated with increased risk of locoregional recurrence after radiation therapy (hazard ratio for locoregional recurrence 2.9-3.2)) in two independent data sets, but there was no difference in locoregional recurrence in triple-negative breast cancer patients not treated with radiation therapy when stratified by androgen receptor expression. In multivariable analysis, androgen receptor expression was most significantly associated with worse local recurrence-free survival after radiation therapy (hazard ratio of 3.58) suggesting that androgen receptor expression may be a biomarker of radiation response in triple-negative breast cancer. Inhibition of androgen receptor with MDV3100 (enzalutamide) induced radiation sensitivity (enhancement ratios of 1.22-1.60) in androgen receptor-positive triple-negative breast cancer lines, but did not affect androgen receptor-negative triple-negative breast cancer or estrogen-receptor-positive, androgen receptor-negative breast cancer cell lines. androgen receptor inhibition with MDV3100 significantly radiosensitized triple-negative breast cancer xenografts in mouse models and markedly delayed tumor doubling/tripling time and tumor weight. Radiosensitization was at least partially dependent on impaired dsDNA break repair mediated by DNA protein kinase catalytic subunit. Our results implicate androgen receptor as a mediator of radioresistance in breast cancer and identify androgen receptor inhibition as a potentially effective strategy for the treatment of androgen receptor-positive radioresistant tumors

In situ characterization of cofacial Co(IV) centers in Co_4O_4 cubane: Modeling the high-valent active site in oxygen-evolving catalysts

The Co_4O_4 cubane is a representative structural model of oxidic cobalt oxygen-evolving catalysts (Co-OECs). The Co-OECs are active when residing at two oxidation levels above an all-Co(III) resting state. This doubly oxidized Co(IV)_2 state may be captured in a Co(III)_2(IV)_2 cubane. We demonstrate that the Co(III)_2(IV)_2 cubane may be electrochemically generated and the electronic properties of this unique high-valent state may be probed by in situ spectroscopy. Intervalence charge-transfer (IVCT) bands in the near-IR are observed for the Co(III)_2(IV)_2 cubane, and spectroscopic analysis together with electrochemical kinetics measurements reveal a larger reorganization energy and a smaller electron transfer rate constant for the doubly versus singly oxidized cubane. Spectroelectrochemical X-ray absorption data further reveal systematic spectral changes with successive oxidations from the cubane resting state. Electronic structure calculations correlated to experimental data suggest that this state is best represented as a localized, antiferromagnetically coupled Co(IV)_2 dimer. The exchange coupling in the cofacial Co(IV)_2 site allows for parallels to be drawn between the electronic structure of the Co_4O_4 cubane model system and the high-valent active site of the Co-OEC, with specific emphasis on the manifestation of a doubly oxidized Co(IV)_2 center on O-O bond formation

Tracking the State and Behavior of People in Response to COVID-1 19 Through the Fusion of Multiple Longitudinal Data Streams

The changing nature of the COVID-19 pandemic has highlighted the importance of comprehensively considering its impacts and considering changes over time. Most COVID-19 related research addresses narrowly focused research questions and is therefore limited in addressing the complexities created by the interrelated impacts of the pandemic. Such research generally makes use of only one of either 1) actively collected data such as surveys, or 2) passively collected data. While a few studies make use of both actively and passively collected data, only one other study collects it longitudinally. Here we describe a rich panel dataset of active and passive data from U.S. residents collected between August 2020 and July 2021. Active data includes a repeated survey measuring travel behavior, compliance with COVID-19 mandates, physical health, economic well-being, vaccination status, and other factors. Passively collected data consists of all locations visited by study participants, taken from smartphone GPS data. We also closely tracked COVID-19 policies across counties of residence throughout the study period. Such a dataset allows important research questions to be answered; for example, to determine the factors underlying the heterogeneous behavioral responses to COVID-19 restrictions imposed by local governments. Better information about such responses is critical to our ability to understand the societal and economic impacts of this and future pandemics. The development of this data infrastructure can also help researchers explore new frontiers in behavioral science. The article explains how this approach fills gaps in COVID-19 related data collection; describes the study design and data collection procedures; presents key demographic characteristics of study participants; and shows how fusing different data streams helps uncover behavioral insights

Toward an integrative understanding of social behavior: new models and new opportunities.

Social interactions among conspecifics are a fundamental and adaptively significant component of the biology of numerous species. Such interactions give rise to group living as well as many of the complex forms of cooperation and conflict that occur within animal groups. Although previous conceptual models have focused on the ecological causes and fitness consequences of variation in social interactions, recent developments in endocrinology, neuroscience, and molecular genetics offer exciting opportunities to develop more integrated research programs that will facilitate new insights into the physiological causes and consequences of social variation. Here, we propose an integrative framework of social behavior that emphasizes relationships between ultimate-level function and proximate-level mechanism, thereby providing a foundation for exploring the full diversity of factors that underlie variation in social interactions, and ultimately sociality. In addition to identifying new model systems for the study of human psychopathologies, this framework provides a mechanistic basis for predicting how social behavior will change in response to environmental variation. We argue that the study of non-model organisms is essential for implementing this integrative model of social behavior because such species can be studied simultaneously in the lab and field, thereby allowing integration of rigorously controlled experimental manipulations with detailed observations of the ecological contexts in which interactions among conspecifics occur

Detection of high-valent iron species in alloyed oxidic cobaltates for catalysing the oxygen evolution reaction

Iron alloying of oxidic cobaltate catalysts results in catalytic activity for oxygen evolution on par with Ni-Fe oxides in base but at much higher alloying compositions. Zero-field ⁵⁷Fe Mössbauer spectroscopy and X-ray absorption spectroscopy (XAS) are able to clearly identify Fe⁴⁺ in mixed-metal Co-Fe oxides. The highest Fe⁴⁺ population is obtained in the 40–60% Fe alloying range, and XAS identifies the ion residing in an octahedral oxide ligand field. The oxygen evolution reaction (OER) activity, as reflected in Tafel analysis of CoFeOx films in 1 M KOH, tracks the absolute concentration of Fe⁴⁺. The results reported herein suggest an important role for the formation of the Fe⁴⁺ redox state in activating cobaltate OER catalysts at high iron loadings

Triamidoamine-supported zirconium: Hydrogen activation, Lewis acidity, and: Rac -lactide polymerization

Investigation of a triamidoamine-supported zirconium hydride intermediate, important to a range of catalytic reactions, revealed the potential Lewis acidity of [κ5-N,N,N,N,C-(Me3SiNCH2CH2)2NCH2CH2NSiMe2CH2]Zr (1). A preliminary study of 1 as a precursor for the polymerization of rac-lactide showed modest activity but indicated that five-coordinate zirconium complexes with tetra-N donor ligands may be an avenue for further development in group 4 metal lactide polymerization catalysis