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Although forgetting is usually considered a memory error, intentional forgetting can function as an adaptive mechanism. The current study examined the effect of increased processing time on directed forgetting in aging as a mechanism to compensate for age-related forgetting. Specifically, an item-method directed forgetting paradigm was used in conjunction with Remember/Know/New responding to examine the effect of cue duration (1, 3, 5 s) on directed forgetting and remembering in younger and older adults. Results indicated that increased processing time improved performance in both age groups. Critically, older adults exhibited a linear increase in directed remembering performance across all cue durations which was related to individual differences in cognitive reserve. Specifically, those older adults with the highest levels of cognitive functioning showed the greatest memory benefit in the longest cue duration condition. These findings indicate the importance of processing time in accounting for intentional memory performance in older adults.The research presented here examined the relationship between the onset of the COVID-19 pandemic, social group identity, intergroup contact, and prejudice. Utilizing a common ingroup identity approach, two datasets, which were composed of data from university students collected via online questionnaires before and after the onset of COVID-19, were combined (N = 511). Participants identified as either one of two subordinate student identities domestic (i.e. AZD1480 molecular weight U.S. citizen or permanent resident) or international (i.e. non-U.S. citizen or foreign resident), then reported on the strength of their subordinate and superordinate identity (university identity). Participants also reported on their contact experiences with outgroup members, outgroup stereotypes, and completed a novel intergroup bias task. Results indicated that after the onset of the pandemic, participants more strongly identified with the superordinate group, which predicted greater perceived intergroup contact and lower intergroup bias. Theoretical implications and future directions are discussed.Inhibition of primary root (PR) growth is a typical developmental response of Arabidopsis to phosphate (Pi) deficiency. Functional disruption of SIZ1, a SUMO E3 ligase, is known to enhance the Pi deficiency-induced inhibition of PR growth. The molecular mechanism of how SIZ1 regulates PR growth under Pi deficiency, however, remains unknown. SIZ1 was recently reported to partially SUMOylate STOP1, a transcription factor that functions in plant tolerance to aluminum toxicity and in plant responses to Pi deficiency by regulating the expression of ALMT1. ALMT1 encodes an aluminum-activated malate transporter, and its expression is induced by Pi deficiency. In siz1, the expression of ALMT1 is enhanced and the removal of Fe from Pi-deficient medium suppressed the siz1 mutant phenotype. In this report, we show that siz1 overaccumulates Fe in its root apoplasts, and consequently, produces more hydroxyl radicals, which are detrimental to root growth. Such physiological changes in siz1 can be completely suppressed by the mutation of STOP1 or ALMT1. Based on previously published work and the results of the current study, we propose that SIZ1 regulates Pi deficiency-mediated PR growth through modulating the accumulation of Fe and the production of hydroxyl radicals by controlling ALMT1 expression.Hepatitis C virus (HCV) is responsible for a variety of human life-threatening diseases, which include liver cirrhosis, chronic hepatitis, fibrosis and hepatocellular carcinoma (HCC) . Computational study of protein-protein interactions between human and HCV could boost the findings of antiviral drugs in HCV therapy and might optimize the treatment procedures for HCV infections. In this analysis, we constructed a prediction model for protein-protein interactions between HCV and human by incorporating the features generated by pseudo amino acid compositions, which were then carried out at two levels categories and features. In brief, extra-tree was initially used for feature selection while SVM was then used to build the classification model. After that, the most suitable models for each category and each feature were selected by comparing with the three ensemble learning algorithms, that is, Random Forest, Adaboost, and Xgboost. According to our results, profile-based features were more suitable for building predictive models among the four categories. AUC value of the model constructed by Xgboost algorithm on independent data set could reach 92.66%. Moreover, Distance-based Residue, Physicochemical Distance Transformation and Profile-based Physicochemical Distance Transformation performed much better among the 17 features. AUC value of the Adaboost classifier constructed by Profile-based Physicochemical Distance Transformation on the independent dataset achieved 93.74%. Taken together, we proposed a better model with improved prediction capacity for protein-protein interactions between human and HCV in this study, which could provide practical reference for further experimental investigation into HCV-related diseases in future.Communicated by Ramaswamy H. Sarma.Single-vehicle, run-off-road (SVROR) crashes account for a significant portion of all road-related injuries and fatalities worldwide. However, no previous study has examined to what extent roadside design guidelines have been applied, nor (and most importantly) whether having a compliant roadside design reduces the likelihood of fatal injury occurrence in SVROR crashes. Thus, the objectives of this research are i) to examine the level of roadside design compliance within the studied area based on the selected benchmark and ii) to investigate whether roadside design compliance reduces the likelihood of fatal injury occurrence in SVROR crashes. Findings from this study are based on extensive crash and field data collected from 1,070 SVROR injury collisions and locations, respectively. The study shows that i) only 32 percent of the studied locations contained compliant design, and ii) barrier and discrete-obstacle lateral offsets larger than 6 and 12 meters, respectively, tended to lower fatality risk. The 12-meter clear-zone (CZ) width is larger than that recommended by previous research, which has based CZ width recommendations also on cost-benefit procedures and not just on fatality risk reduction.
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