The Ethics of Unlocking a Billion More Brains

Online programs that engage a global audience are often promoted as “democratizing” education worldwide. However, the ethics of expecting students globally to conform to Western academic values and processes is largely ignored. Until programs are designed and delivered with cultural intelligence and humility, their full value will be compromised

Identification of Consumer Adverse Drug Reaction Messages on Social Media

The prevalence of social media has resulted in spikes of data on the Internet which can have potential use to assist in many aspects of human life. One prospective use of the data is in the development of an early warning system to monitor consumer Adverse Drug Reactions (ADRs). The direct reporting of ADRs by consumers is playing an increasingly important role in the world of pharmacovigilance. Social media provides patients a platform to exchange their experiences regarding the use of certain drugs. However, the messages posted on those social media networks contain both ADR related messages (positive examples) and non-ADR related messages (negative examples). In this paper, we integrate text mining and partially supervised learning methods to automatically extract and classify messages posted on social media networks into positive and negative examples. Our findings can provide managerial insights into how social media analytics can improve not only postmarketing surveillance, but also other problem domains where large quantity of user-generated content is available

Ethical leadership and follower voice and performance: the role of follower identifications and entity morality beliefs

Previous studies have investigated a number of psychological mechanisms that mediate the relationships between ethical leaderships and follower outcomes. Follower organizational identification has been found to mediate the relationship between ethical leadership and follower job performance. In this research, we incorporate a second distinct and theoretically important type of social identification process, relational identification with the leader, and examine their mediating effects on follower performance and voice outcomes. Further, we bring the implicit theory of morality to the behavioral ethics literature and examine follower morality beliefs as a moderator. Using a Romanian sample, we found that ethical leadership has an indirect effect on follower job performance and voice (through the mediating mechanisms of both organizational and relational identifications) and that these relationships are stronger for followers who held the implicit theory that a person’s moral character is fixed. Theoretical and practical implications are discussed

Clustering, host halos and environment of z∼\sim2 galaxies as a function of their physical properties

Using a sample of 25683 star-forming and 2821 passive galaxies at $z\sim2$, selected in the COSMOS field following the BzK color criterion, we study the hosting halo mass and environment of galaxies as a function of their physical properties. Spitzer and Herschel provide accurate SFR estimates for starburst galaxies. We measure the auto- and cross-correlation functions of various galaxy sub-samples and infer the properties of their hosting halos using both an HOD model and the linear bias at large scale. We find that passive and star-forming galaxies obey a similarly rising relation between the halo and stellar mass. The mean host halo mass of star forming galaxies increases with the star formation rate between 30 and 200 M$_\odot$.yr$^{-1}$, but flattens for higher values, except if we select only main-sequence galaxies. This reflects the expected transition from a regime of secular co-evolution of the halos and the galaxies to a regime of episodic starburst. We find similar large scale biases for main-sequence, passive, and starburst galaxies at equal stellar mass, suggesting that these populations live in halos of the same mass. We detect an excess of clustering on small scales for passive galaxies and showed, by measuring the large-scale bias of close pairs, that this excess is caused by a small fraction ($\sim16$) of passive galaxies being hosted by massive halos ($\sim 3 \times 10^{13}$ M$_\odot$) as satellites. Finally, extrapolating the growth of halos hosting the z$\sim$2 population, we show that M$_\star \sim 10^{10}$ M$_\odot$ galaxies at z$\sim$2 will evolve, on average, into massive (M$_\star \sim 10^{11}$ M$_\odot$), field galaxies in the local Universe and M$_\star \sim 10^{11}$ M$_\odot$ galaxies at z=2 into local, massive, group galaxies. The most massive main-sequence galaxies and close pairs of massive, passive galaxies end up in today's clusters.Comment: 18 pages, 16 figures, Accepted by A&

High pressure induced precipitation in Al7075 alloy

Precipitate-matrix interactions govern the mechanical behavior of precipitate strengthened Al-based alloys. These alloys find a wide range of applications ranging from aerospace to automobile and naval industries due to their low cost and high strength to weight ratio. Structures made from Al-based alloys undergo complex loading conditions such as high strain rate impact, which involves high pressures. Here we use diamond anvil cells to study the behavior of Al-based Al7075 alloy under quasi-hydrostatic and non-hydrostatic pressure up to ~53 GPa. In situ X-ray diffraction (XRD) and pre- and post-compression transmission electron microscopy (TEM) imaging are used to analyze microstructural changes and estimate high pressure strength. We find a bulk modulus of 75.2 +- 1.9 GPa using quasi-hydrostatic pressure XRD measurements. XRD showed that non-hydrostatic pressure leads to a significant increase in defect density and peak broadening with pressure cycling. XRD mapping under non-hydrostatic pressure revealed that the region with the highest local pressure had the greatest increase in defect nucleation, whereas the region with the largest local pressure gradient underwent texturing and had larger grains. TEM analysis showed that pressure cycling led to the nucleation and growth of many precipitates. The significant increase in defect and precipitate density leads to an increase in strength for Al7075 alloy at high pressures.Comment: 15 pages, 5 figure

Population pharmacokinetics of trastuzumab emtansine (T-DM1), a HER2-targeted antibody–drug conjugate, in patients with HER2-positive metastatic breast cancer: clinical implications of the effect of covariates

PURPOSE: Trastuzumab emtansine (T-DM1) is an antibody–drug conjugate comprising the humanized monoclonal antibody trastuzumab linked to DM1, a highly potent cytotoxic agent. A population pharmacokinetic (PK) analysis was performed to estimate typical values and interindividual variability of T-DM1 PK parameters and the effects of clinically relevant covariates. METHODS: Serum samples were collected from 671 patients with human epidermal growth factor receptor 2-positive locally advanced or metastatic breast cancer (MBC) who received single-agent T-DM1 in five phase I to phase III studies. Nonlinear mixed-effects modeling with the first-order conditional estimation method was used. RESULTS: A linear two-compartment model with first-order elimination from the central compartment described T-DM1 PKs in the clinical dose range. T-DM1 elimination clearance was 0.676 L/day, volume of distribution in the central compartment (V(c)) was 3.127 L, and terminal elimination half-life was 3.94 days. Age, race, region, and renal function did not influence T-DM1 PK. Given the low-to-moderate effect of all statistically significant covariates on T-DM1 exposure, none of these covariates is expected to result in a clinically meaningful change in T-DM1 exposure. CONCLUSIONS: T-DM1 PK properties are consistent and predictable in patients. A further refinement of dose based on baseline covariates other than body weight for the current 3.6 mg/kg regimen would not yield clinically meaningful reductions in interindividual PK variability in patients with MBC. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00280-014-2500-2) contains supplementary material, which is available to authorized users

Normalization and Statistical Analysis of Multiplexed Bead-Based Immunoassay Data Using Mixed-Effects Modeling

Multiplexed bead-based flow cytometric immunoassays are a powerful experimental tool for investigating cellular communication networks, yet their widespread adoption is limited in part by challenges in robust quantitative analysis of the measurements. Here we report our application of mixed-effects modeling for the normalization and statistical analysis of bead-based immunoassay data. Our data set consisted of bead-based immunoassay measurements of 16 phospho-proteins in lysates of HepG2 cells treated with ligands that regulate acute-phase protein secretion. Mixed-effects modeling provided estimates for the effects of both the technical and biological sources of variance, and normalization was achieved by subtracting the technical effects from the measured values. This approach allowed us to detect ligand effects on signaling with greater precision and sensitivity and to more accurately characterize the HepG2 cell signaling network using constrained fuzzy logic. Mixed-effects modeling analysis of our data was vital for ascertaining that IL-1α and TGF-α treatment increased the activities of more pathways than IL-6 and TNF-α and that TGF-α and TNF-α increased p38 MAPK and c-Jun N-terminal kinase (JNK) phospho-protein levels in a synergistic manner. Moreover, we used mixed-effects modeling-based technical effect estimates to reveal the substantial variance contributed by batch effects along with the absence of loading order and assay plate position effects. We conclude that mixed-effects modeling enabled additional insights to be gained from our data than would otherwise be possible and we discuss how this methodology can play an important role in enhancing the value of experiments employing multiplexed bead-based immunoassays.United States. Army Research Office (Contract W911NF-09-D-0001)National Institutes of Health (U.S.) (NIH P50-GM68762

Engineered IL-7 synergizes with IL-12 immunotherapy to prevent T cell exhaustion and promote memory without exacerbating toxicity

Cancer immunotherapy is moving toward combination regimens with agents of complementary mechanisms of action to achieve more frequent and robust efficacy. However, compared with single-agent therapies, combination immunotherapies are associated with increased overall toxicity because the very same mechanisms also work in concert to enhance systemic inflammation and promote off-tumor toxicity. Therefore, rational design of combination regimens that achieve improved antitumor control without exacerbated toxicity is a main objective in combination immunotherapy. Here, we show that the combination of engineered, tumor matrix-binding interleukin-7 (IL-7) and IL-12 achieves remarkable anticancer effects by activating complementary pathways without inducing any additive immunotoxicity. Mechanistically, engineered IL-12 provided effector properties to T cells, while IL-7 prevented their exhaustion and boosted memory formation as assessed by tumor rechallenge experiments. The dual combination also rendered checkpoint inhibitor (CPI)–resistant genetically engineered melanoma model responsive to CPI. Thus, our approach provides a framework of evaluation of rationally designed combinations in immuno-oncology and yields a promising therapy

An oligotrophic deep-subsurface community dependent on syntrophy is dominated by sulfur-driven autotrophic denitrifiers

Subsurface lithoautotrophic microbial ecosystems (SLiMEs) under oligotrophic conditions are typically supported by H₂. Methanogens and sulfate reducers, and the respective energy processes, are thought to be the dominant players and have been the research foci. Recent investigations showed that, in some deep, fluid-filled fractures in the Witwatersrand Basin, South Africa, methanogens contribute <5% of the total DNA and appear to produce sufficient CH₄ to support the rest of the diverse community. This paradoxical situation reflects our lack of knowledge about the in situ metabolic diversity and the overall ecological trophic structure of SLiMEs. Here, we show the active metabolic processes and interactions in one of these communities by combining metatranscriptomic assemblies, metaproteomic and stable isotopic data, and thermodynamic modeling. Dominating the active community are four autotrophic β-proteobacterial genera that are capable of oxidizing sulfur by denitrification, a process that was previously unnoticed in the deep subsurface. They co-occur with sulfate reducers, anaerobic methane oxidizers, and methanogens, which each comprise <5% of the total community. Syntrophic interactions between these microbial groups remove thermodynamic bottlenecks and enable diverse metabolic reactions to occur under the oligotrophic conditions that dominate in the subsurface. The dominance of sulfur oxidizers is explained by the availability of electron donors and acceptors to these microorganisms and the ability of sulfur-oxidizing denitrifiers to gain energy through concomitant S and H₂ oxidation. We demonstrate that SLiMEs support taxonomically and metabolically diverse microorganisms, which, through developing syntrophic partnerships, overcome thermodynamic barriers imposed by the environmental conditions in the deep subsurface

The ocean sampling day consortium

Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world’s oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits