Introduction Purpose orientation has an important impact on the development of adolescence. An effective instrument is needed to describe the purpose orientation of youth. The aim of this research is to develop a reliable and valid scale to measure life purpose orientations of youth. Methods Study 1 established a preliminary pool of items based on a literature review, an open-form questionnaire, and some expert opinions. Study 2 used exploratory factor analysis and performed internal consistency and reliability tests. The sample consisted of 442 young Chinese students, divided into males (49.3%) and females (50.7%) with an age range of 13 to 22 years. Study 3 performed confirmatory factor analysis and tested the scale’s calibration validity and test-retest reliability. The confirmatory sample comprised 91,635 young Chinese students, divided into males (43.2%) and females (56.5%) with an age range of 12 to 23 years. The calibration validity sample consisted of 572 participants, aged 12 to 22. The test-retest reliability sample consisted of 200 participants. Results Through exploratory factor analysis, the four-factor structure revealed contains personal growth, social promotion, family well-being, and personal well-being purpose orientations. This four factor-structure revealed a 65.26% cumulative variance. The four factors’ alpha reliability was 0.89 for personal growth, 0.87 for social promotion, 0.86 for family well-being, and 0.87 for personal well-being, respectively. Confirmatory factor analysis showed that the model fitting index had a good four-factor structure. The calibration validity and test-retest reliability were acceptable. Conclusion These findings demonstrated that the 19-item findings demonstrated that the Youth Purpose Orientation Scale is a valid and reliable measure. In future research, it can be used to measure purpose orientation in youth.

It has been challenging to integrate various medical imaging modalities into an ultra-small nanoparticle with good biocompatibility to build highly efficient multimodal imaging nanoprobes. A new manganese and dysprosium codoped carbon quantum dots (Mn,Dy-CQDs) with a mean diameter of 1.77 nm was synthesized for fluorescence imaging, T1/T2-weighted magnetic resonance imaging (T1/T2-weighted MRI), and x-ray computed tomography (CT) imaging using a simple onestep hydrothermal approach. The obtained Mn,Dy-CQDs showed good water solubility, long-term stability, strong stable fluorescence property (fluorescence quantum yield of 31.62%), and excellent biocompatibility. The cell imaging verified that the Mn,Dy-CQDs have high efficiency of fluorescence imaging. The Mn,Dy-CQDs, on the other hand, had a superior x-ray absorption performance (47.344 HU l g −1 ), a higher longitudinal relaxivity (r 1 =7.47 mM −1 s −1 ), a higher transverse relaxivity (r 2 =42.686 mM −1 s −1 ). In vitro T1/T2-weighted MRI and CT imaging showed that Mn,Dy-CQDs can produce a strong contrast enhancement impact. To summarise, the Mn,Dy-CQDs may be used as a T1/T2-weighted MRI/CT/fluorescent quadri-modal imaging nanoprobe, indicating that they have a lot of uses in biomedical multimode imaging and clinics.

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Objectives Although previous studies have explored the effect of reward feedback on recognition memory, electrophysiological evidence for reward-enhanced memory and its underlying processing mechanisms remains unclear. Methods This study adopts reward-learning and recognition memory tasks. Participants were asked to learn the reward values of two-color images (each color image had either reward or nonreward feedback) in the reward-learning task, and then tested their recognition memory performance with reward and nonreward feedback items. Results Results demonstrated that the recognition memory performance of rewarded items was better than that of nonrewarded items. During the reward-learning period, nonreward feedback elicited larger feedback-related negativity (FRN) and P300 amplitudes compared with reward feedback. The findings indicated that participants mainly engaged in prediction error processing in the early stage, followed by comparing and context update of the learned items. During the recognition memory period, reward items elicited larger FN400 amplitude and smaller LPC amplitude compared with nonreward items. This suggests that reward item retrieval has deeper memory traces and can identify items faster, relying mainly on familiarity processing. Conversely, nonreward, as a general or inhibitory item, requires more detail and cognitive resources, that is, relies on recollection processing. Conclusions These findings indicated that participants had different process patterns between reward and nonreward items during recognition retrieval.