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Over the last 20 years, online peer review and assessment have become widely used and well-researched practices in education. Their use increased, especially with the proliferation of nonconventional large-scale and online modes of teaching and learning, such as Massive Open Online Courses (MOOCs). A well-designed peer-review system is expected to produce valid and reliable assessments of the artifacts created by participants. These systems notably vary in designs, particularly in the structure of the peer-review networks, i.e., how participants are linked to each other as creators and reviewers. To date, little research has been done on how different network structures impact a system's ability to accurately assess the quality of the evaluated artifacts. We begin to address this gap, using a simulation approach to demonstrate that two network characteristics--dispersion and reciprocity--may indeed affect assessment fidelity in peer-review systems in conjunction with other design choices, such as evaluation scale and aggregation method. We also outline directions for further investigations of peer-review systems design.

ObjectiveAttentional bias (AB) may be one mechanism contributing to the development and/or maintenance of disordered eating. AB has traditionally been measured using reaction time in response to a stimulus. Novel methods for AB measurement include eye tracking to measure visual fixation on a stimulus, and electroencephalography to measure brain activation in response to a stimulus. This systematic review summarizes, critiques, and integrates data on AB gathered using the above-mentioned methods in those with binge eating behaviors, including binge eating, loss of control eating, and bulimia nervosa.MethodLiterature searches on PubMed and PsycInfo were conducted using combinations of terms related to binge eating and biobehavioral AB paradigms. Studies using AB paradigms with three categories of stimuli were included: food, weight/shape, and threat. For studies reporting means and standard deviations of group bias scores, Hedges' g effect sizes for group differences in AB were calculated.ResultsFifty articles met inclusion criteria and were reviewed. Individuals who binge eat in the absence of compensatory behaviors show an increased AB to food cues, but few studies have examined such individuals' AB toward weight/shape and threatening stimuli. Individuals with bulimia nervosa consistently show an increased AB to shape/weight cues and socially threatening stimuli, but findings for AB to food cues are mixed.DiscussionWhile there are important research gaps, preliminary evidence suggests that the combination of AB to disorder-specific cues (i.e., food and weight/shape) and AB toward threat may be a potent contributor to binge eating. This conclusion underscores previous findings on the interaction between negative affect and AB to disorder-specific cues. Recommendations for future research are provided.

KRAS can bind numerous effector proteins, which activate different downstream signaling events. The best known are RAF, phosphatidylinositide (PI)-3' kinase, and RalGDS families, but many additional direct and indirect effectors have been reported. We have assessed how these effectors contribute to several major phenotypes in a quantitative way, using an arrayed combinatorial siRNA screen in which we knocked down 41 KRAS effectors nodes in 92 cell lines. We show that every cell line has a unique combination of effector dependencies, but in spite of this heterogeneity, we were able to identify two major subtypes of KRAS mutant cancers of the lung, pancreas, and large intestine, which reflect different KRAS effector engagement and opportunities for therapeutic intervention.

There is intense interest in developing therapeutic strategies for RAS proteins, the most frequently mutated oncoprotein family in cancer. Development of effective anti-RAS therapies will be aided by the greater appreciation of RAS isoform-specific differences in signaling events that support neoplastic cell growth. However, critical issues that require resolution to facilitate the success of these efforts remain. In particular, the use of well-validated anti-RAS antibodies is essential for accurate interpretation of experimental data. We evaluated 22 commercially available anti-RAS antibodies with a set of distinct reagents and cell lines for their specificity and selectivity in recognizing the intended RAS isoforms and mutants. Reliability varied substantially. For example, we found that some pan- or isoform-selective anti-RAS antibodies did not adequately recognize their intended target or showed greater selectivity for another; some were valid for detecting G12D and G12V mutant RAS proteins in Western blotting, but none were valid for immunofluorescence or immunohistochemical analyses; and some antibodies recognized nonspecific bands in lysates from "Rasless" cells expressing the oncoprotein BRAFV600E Using our validated antibodies, we identified RAS isoform-specific siRNAs and shRNAs. Our results may help to ensure the accurate interpretation of future RAS studies.

Oncogenic Ras mutants play a major role in the etiology of most aggressive and deadly carcinomas in humans. In spite of continuous efforts, effective pharmacological treatments targeting oncogenic Ras isoforms have not been developed. Cell-surface proteins represent top therapeutic targets primarily due to their accessibility and susceptibility to different modes of cancer therapy. To expand the treatment options of cancers driven by oncogenic Ras, new targets need to be identified and characterized at the surface of cancer cells expressing oncogenic Ras mutants. Here, we describe a mass spectrometry-based method for molecular profiling of the cell surface using KRasG12V transfected MCF10A (MCF10A-KRasG12V) as a model cell line of constitutively activated KRas and native MCF10A cells transduced with an empty vector (EV) as control. An extensive molecular map of the KRas surface was achieved by applying, in parallel, targeted hydrazide-based cell-surface capturing technology and global shotgun membrane proteomics to identify the proteins on the KRasG12V surface. This method allowed for integrated proteomic analysis that identified more than 500 cell-surface proteins found unique or upregulated on the surface of MCF10A-KRasG12V cells. Multistep bioinformatic processing was employed to elucidate and prioritize targets for cross-validation. Scanning electron microscopy and phenotypic cancer cell assays revealed changes at the cell surface consistent with malignant epithelial-to-mesenchymal transformation secondary to KRasG12V activation. Taken together, this dataset significantly expands the map of the KRasG12V surface and uncovers potential targets involved primarily in cell motility, cellular protrusion formation, and metastasis.

Oncogenic Ras mutants play a major role in the etiology of most aggressive and deadly carcinomas in humans. In spite of continuous efforts, effective pharmacological treatments targeting oncogenic Ras isoforms have not been developed. Cell-surface proteins represent top therapeutic targets primarily due to their accessibility and susceptibility to different modes of cancer therapy. To expand the treatment options of cancers driven by oncogenic Ras, new targets need to be identified and characterized at the surface of cancer cells expressing oncogenic Ras mutants. Here, we describe a mass spectrometry-based method for molecular profiling of the cell surface using KRasG12V transfected MCF10A (MCF10A-KRasG12V) as a model cell line of constitutively activated KRas and native MCF10A cells transduced with an empty vector (EV) as control. An extensive molecular map of the KRas surface was achieved by applying, in parallel, targeted hydrazide-based cell-surface capturing technology and global shotgun membrane proteomics to identify the proteins on the KRasG12V surface. This method allowed for integrated proteomic analysis that identified more than 500 cell-surface proteins found unique or upregulated on the surface of MCF10A-KRasG12V cells. Multistep bioinformatic processing was employed to elucidate and prioritize targets for cross-validation. Scanning electron microscopy and phenotypic cancer cell assays revealed changes at the cell surface consistent with malignant epithelial-to-mesenchymal transformation secondary to KRasG12V activation. Taken together, this dataset significantly expands the map of the KRasG12V surface and uncovers potential targets involved primarily in cell motility, cellular protrusion formation, and metastasis.

Identifying collaboration between learners in a course is an important challenge in education for two reasons: First, depending on the courses rules, collaboration can be considered a form of cheating. Second, it helps one to more accurately evaluate each learners competence. While such collaboration identification is already challenging in traditional classroom settings consisting of a small number of learners, the problem is greatly exacerbated in the context of both online courses or massively open online courses (MOOCs) where potentially thousands of learners have little or no contact with the course instructor. In this work, we propose a novel methodology for "collaboration-type identification," which both "identifies" learners who are likely collaborating and also "classifies" the type of collaboration employed. Under a fully Bayesian setting, we infer the probability of learners succeeding on a series of test items solely based on graded response data. We then use this information to jointly compute the likelihood that two learners were collaborating and what collaboration model (or type) was used. We demonstrate the efficacy of the proposed methods on both synthetic and real-world educational data; for the latter, the proposed methods find strong evidence of collaboration among learners in two non-collaborative take-home exams.

Objective: Relapse is a major problem in drug addiction treatment. Both drug craving and drug-related cognitions (e.g., attentional bias and implicit attitudes to drugs) may contribute to relapse. Using ecological momentary assessments, we examined whether craving and cognitions assessed during drug detoxification treatment were associated with relapse. Method: Participants were 68 heroin-dependent inpatients undergoing clinical detoxification at an addiction treatment center. Participants carried around a personal digital assistant for 1 week. Participants completed up to 4 random assessments (RAs) per day. They also completed an assessment when they experienced a temptation to use drugs (TA). At each assessment, participants reported their craving and attitudes to drugs. Implicit cognitions were assessed with a drug Stroop task (attentional bias) and an Implicit Association Test (implicit attitudes). Results: Individuals who relapsed during the study week exhibited a larger attentional bias and more positive implicit attitudes to drugs than did nonrelapsers at TAs (but not RAs). In addition, compared to nonrelapsers, relapsers reported higher levels of craving and more positive explicit attitudes to drugs at TAs than at RAs. Additional within-subject analyses revealed that attentional bias for drugs at TAs increased before relapse. Conclusions: Drug-related cognitive processes assessed with ecological momentary assessments were associated with relapse during drug detoxification. Real-time assessment of craving and cognitions may help to identify which individuals are at risk of relapse and when they are at risk of relapse. (Contains 5 tables, 2 figures and 2 footnotes.)

Cue exposure paradigms have been used to examine reactivity to smoking cues. However, it is not known whether cue-provoked craving is associated with smoking cessation outcomes or whether cue reactivity can be attenuated by nicotine replacement therapy (NRT) in clinical samples. Cue-provoked craving ratings and reaction time responses were measured on the 1st day of abstinence among 158 smokers who had been randomized to high-dose nicotine (35 mg) or placebo patch. The nicotine patch reduced overall levels of craving but did not attenuate cue-provoked craving increases or reaction time responses. Cue-provoked craving predicted relapse among participants on the nicotine patch but not among those on placebo. In summary, NRT users could benefit from treatment that attenuates cue-provoked craving.

Relapse is a central problem in smoking treatment. Data collected at the time of relapse episodes indicate that stress and negative affect (NA) promote relapse, but retrospective data are potentially biased. The authors performed a prospective analysis of stress and NA prior to initial lapses in smokers (N = 215). Day-to-day changes in stress (daily negative and positive events and Perceived Stress Scale scores) and NA (multiple momentary affect ratings) did not predict lapse risk on the following day. However, within the lapse day itself, NA was already significantly increasing hours before lapses, but only for episodes attributed to stress or bad mood. Thus, rapid increases in NA, but not slow-changing shifts in stress and NA, were associated with relapse.