Age-related valence-based reversal in recruitment of medial prefrontal cortex on a visual search task

Previous behavioral research has revealed a positivity effect that occurs with aging, with older adults focusing more on positive information and less on negative emotional stimuli as compared to young adults. Questions have been raised as to whether this effect exists in the rapid detection of information or whether it operates only at later stages of processing. In the present study, we used eye-tracking and neuroimaging methodologies to examine whether the two age groups accomplished the detection of emotional information on a visual search task using the same mechanisms. Eye-tracking results revealed no significant age differences in detection or viewing time of emotional targets as a function of valence. Despite their general similarity in task performance, neuroimaging results revealed an age-related valence-based reversal in medial prefrontal cortex (MPFC) activity, with detection of negative compared to positive targets activating the MPFC more for younger adults, and detection of positive compared to negative targets activating the MPFC more for older adults. These results suggest that age-related valence reversals in neural activity can exist even on tasks that require only relatively automatic processing of emotional information.     

遗传算法与变邻域搜索混合模型在护士排班中的应用

目的在探讨基于层级管理的护士APN排班模型的基础上,引入具有精确的全局搜索能力的遗传算法与变邻域搜索混合模型来解决护士排班过程中人员层级复杂、不同班次人员需求量不同等问题。方法首先,初始化排班表,然后利用遗传算法对初始化的排班表进行搜索,得到一个初步的排班表,最后利用变邻域搜索优化排班表,得到满足要求的排班表。结果使用该混合模型得到的排班表,能满足每日护士的人数需求和每名护士的工作量要求。同时,基于层级管理,各层级护士分开排班,能降低排班难度,在增加护士人员时,效率仍然较高。结论遗传算法与变邻域搜索的混合模型能解决护士排班中的各种复杂问题,是一种符合实际需求的模型。基于此模型来编制护士排班软件,能提升护理工作效率和满意度,便于对护理人员进行量化考核统计分析。     

Seasonal and Geographic Patterns in Seeking Cardiovascular Health Information: An Analysis of the Online Search Trends

Objective

To ascertain whether temporal and geographic interest in seeking cardiovascular disease (CVD) information online follows seasonal and geographic patterns similar to those observed in real-world data.

Functional brain connectivity and cognition: effects of adult age and task demands

Previous neuroimaging research has documented that patterns of intrinsic (resting state) functional connectivity (FC) among brain regions covary with individual measures of cognitive performance. Here, we examined the relation between intrinsic FC and a reaction time (RT) measure of performance, as a function of age group and task demands. We obtained filtered, event-related functional magnetic resonance imaging data, and RT measures of visual search performance, from 21 younger adults (19–29 years old) and 21 healthy, older adults (60–87 years old). Age-related decline occurred in the connectivity strength in multiple brain regions, consistent with previous findings. Among 8 pairs of regions, across somatomotor, orbitofrontal, and subcortical networks, increasing FC was associated with faster responding (lower RT). Relative to younger adults, older adults exhibited a lower strength of this RT-connectivity relation and greater disruption of this relation by a salient but irrelevant display item (color singleton distractor). Age-related differences in the covariation of intrinsic FC and cognitive performance vary as a function of task demands.     

Defensins: Natural component of human innate immunity

The widespread use of antibiotics has contributed to a huge increase in the number of resistant bacteria. New classes of drugs are therefore being developed of which defensins are a potential source. Defensins are a group of antimicrobial peptides found in different living organisms, involved in the first line of defense in their innate immune response against pathogens. This review summarizes the results of studies of this family of human antimicrobial peptides (AMPs). There is a special emphasis on describing the entire group and individual peptides, history of their discovery, their functions and expression sites. The results of the recent studies on the use of the biologically active peptides in human medicine are also presented. The pharmaceutical potential of human defensins cannot be ignored, especially considering their strong antimicrobial activity and properties such as low molecular weight, reduced immunogenicity, broad activity spectrum and resistance to proteolysis, but there are still many challenges and questions regarding the possibilities of their practical application.     

Attentional capture during visual search is attenuated by target predictability: Evidence from the N2pc,Pd, and topographic segmentation

Attentional capture by salient distractors has been confirmed by the occurrence of an N2pc to the salient distractor. To clarify some failures to replicate this finding, we varied target predictability to induce different search modes. In the unpredictable target condition, the target shape varied randomly from trial to trial, favoring singleton detection mode. In the predictable target condition, the target shape remained the same in a block of trials, favoring feature search mode. With unpredictable targets, we observed an N2pc toward the salient color distractor, confirming attentional capture in singleton search mode. With predictable targets, there was no N2pc to the salient distractor, but a distractor positivity (Pd), suggesting distractor suppression. Also, differences emerged in the topographic segmentation of N2pc and Pd. Further, the amplitude of the N2pc toward the target was larger with predictable than with unpredictable targets.     

Disulfide connectivity prediction based on structural information without a prior knowledge of the bonding state of cysteines

Previous studies predicted the disulfide bonding patterns of cysteines using a prior knowledge of their bonding states. In this study, we propose a method that is based on the ensemble support vector machine (SVM), with the structural features of cysteines extracted without any prior knowledge of their bonding states. This method is useful for improving the predictive performance of disulfide bonding patterns. For comparison, the proposed method was tested with the same dataset SPX that was adopted in previous studies. The experimental results demonstrate that bridge classification and disulfide connectivity predictions achieve 96.5% and 89.2% accuracy, respectively, using the ensemble SVM model, which outperforms the traditional method (51.5% and 51.0%, respectively) and the model that is based on a single-kernel SVM classifier (94.6% and 84.4%, respectively). For protein chain and residue classifications, the sensitivity, specificity, and accuracy of ensemble and single-kernel SVM approaches are better than those of the traditional methods. The predictive performances of the ensemble SVM and single-kernel models are identical, indicating that the ensemble model can converge to the single-kernel model for some applications.