J Huang

Mixed lineage leukemia (MLL) fusion protein (FP)‐induced acute leukemia is highly aggressive and often refractory to therapy. Recent progress in the field has unraveled novel mechanisms and targets to combat this disease. Menin, a nuclear protein, interacts with wild‐type (WT) MLL, MLL‐FPs, and other partners such as the chromatin‐associated protein LEDGF and the transcription factor C‐Myb to promote leukemogenesis. The newly solved co‐crystal structure illustrating the menin–MLL interaction, coupled with the role of menin in recruiting both WT MLL and MLL‐FPs to target genes, highlights menin as a scaffold protein and a central hub controlling this type of leukemia. The menin/WT MLL/MLL‐FP hub may also cooperate with several signaling pathways, including Wnt, GSK3, and bromodomain‐containing Brd4‐related pathways to sustain MLL‐FP‐induced leukemogenesis, revealing new therapeutic targets to improve the treatment of MLL‐FP leukemias.

The significance of horizontal gene transfer (HGT) in eukaryotic evolution remains controversial. Although many eukaryotic genes are of bacterial origin, they are often interpreted as being derived from mitochondria or plastids. Because of their fixed gene pool and gene loss, however, mitochondria and plastids alone cannot adequately explain the presence of all, or even the majority, of bacterial genes in eukaryotes. Available data indicate that no insurmountable barrier to HGT exists, even in complex multicellular eukaryotes. In addition, the discovery of both recent and ancient HGT events in all major eukaryotic groups suggests that HGT has been a regular occurrence throughout the history of eukaryotic evolution. A model of HGT is proposed that suggests both unicellular and early developmental stages as likely entry points for foreign genes into multicellular eukaryotes.

Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for understanding the mechanism of programmed cell death, and their function is related to their types. According to the classification scheme by Zhou and Doctor (2003), the apoptosis proteins are categorized into the following four types: (1) cytoplasmic protein; (2) plasma membrane-bound protein; (3) mitochondrial inner and outer proteins; (4) other proteins. A powerful learning machine, the Support Vector Machine, is applied for predicting the type of a given apoptosis protein by incorporating the sqrt-amino acid composition effect. High success rates were obtained by the re-substitute test (98/98 = 100 %) and the jackknife test (89/98 = 90.8%).

As a worldwide epidemic in the digital age, cyberbullying is a pertinent but understudied concern—especially from the perspective of language. Elucidating the linguistic features of cyberbullying is critical both to preventing it and to cultivating ethical and responsible digital citizens. In this study, a mixed-method approach integrating lexical feature analysis, sentiment polarity analysis, and semantic network analysis was adopted to develop a deeper understanding of cyberbullying language. Five cyberbullying cases on Chinese social media were analyzed to uncover explicit and implicit linguistic features. Results indicated that cyberbullying comments had significantly different linguistic profiles than non-bullying comments and that explicit and implicit bullying were distinct. The content of cases further suggested that cyberbullying language varied in the use of words, types of cyberbullying, and sentiment polarity. These findings offer useful insight for designing automatic cyberbullying detection tools for Chinese social networking platforms. Implications also offer guidance for regulating cyberbullying and fostering ethical and responsible digital citizens.

Understanding the influencing factors of cyberbullying is key to effectively curbing cyberbullying. Among the various factors, this study focused on the personal level of individual students and categorized the influencing factors of cyberbullying among college students into five sublevels, i.e., background, Internet use and social network habits, personality, emotion, and literacy related to digital citizenship. Then a questionnaire survey was applied to 947 Chinese college students. The results show that cyberbullying among Chinese college students are generally at a low level. There are many factors influence cyberbullying. Specifically, at the personal background level, gender has a significant impact on cyberbullying and being cyberbullied. In terms of personal Internet use and social network habits, students’ average daily online time has no significant correlation with cyberbullying and being cyberbullied; however, the proportion of online non-learning time has a significantly positive correlation with cyberbullying, and the proportion of online learning/work time has a significant impact on being cyberbullied. At the personality level, the Big Five personality traits have varying degrees of correlation with and influence on cyberbullying and being cyberbullied. At the personal emotions level, students’ life satisfaction has a significantly negative correlation with cyberbullying and being cyberbullied while it only has a significant impact on being cyberbullied; the personal stress and empathetic concern aspects of empathy have a significantly positive correlation with cyberbullying and being cyberbullied among female students. At the literacy related to digital citizenship level, students’ understanding of and compliance with Internet etiquette have significantly negative impacts on cyberbullying; the ability to communicate and collaborate online and Internet addiction have significantly positive impacts on cyberbullying and being cyberbullied; the understanding of and compliance with relevant digital laws and regulations have significantly negative correlations with cyberbullying and being cyberbullied. Overall, college students’ digital citizenship level has a significantly negative correlation with cyberbullying but no significant correlation with being cyberbullied. Finally, analysis and suggestions were provided according to these statistical results and the effects of these factors on cyberbullying and being cyberbullied among college students, so as to help solve this problem and provide a new perspective for research in this field.

For understanding and controlling spreading in complex networks, identifying the most influential nodes, which can be applied to disease control, viral marketing, air traffic control, and many other fields, is of great importance. By taking the effect of the spreading rate on information entropy into account, we proposed an improved information entropy method. Compared to the benchmark methods in the six different empirical networks, the IIE method has been found with a better performance on Kendall’s Tau and imprecision function under the Susceptible Infected Recovered model. Especially in the Facebook network, Kendall’s Tau can grow by 120% as compared with the original IE method. And, there is also an equally good performance in the comparative analysis of imprecise functions. The imprecise functions’ value of the IIE method is smaller than the benchmark methods in six networks.

The process dissociation procedure (PDP) of implicit sequence learning states that the correct inclusion-task response contains the incorrect exclusion-task response. However, there has been no research to test the hypothesis. The current study used a single variable (Stimulus Onset Asynchrony SOA: 850 ms vs. 1350 ms) between-subjects design, with pre-task resting-state fMRI, to test and improve the classical PDP to the mutually exclusive theory (MET). (1) Behavioral data and neuroimaging data demonstrated that the classical PDP has not been validated. In the SOA = 850 ms group, the correct inclusion-task response was at chance, but the incorrect exclusion-task response occurred greater than chance. In the SOA = 850 ms group, the two responses were not correlated, but in the SOA = 1,350 ms group and putting the two groups together, the two responses were in contrast to each other. In each group, brain areas whose amplitude of low frequency fluctuations (ALFFs) in the resting-state related to the two responses were either completely different or opposite to one another. However, the results were perfectly consistent with the MET proposed by the present study which suggests that the correct inclusion-task response is equal to the correct exclusion-task response is equal toC+A1, and the incorrect exclusion-task response is equal toA2.Cdenotes the controlled response andA1andA2denote two different automatic responses. (2) The improved PDP was proposed to categorize the 12 kinds of triplets as delineating four knowledge types, namely non-acquisition of knowledge, uncontrollable knowledge, half-controllable knowledge, and controllable knowledge with the MET. ALFFs in the resting-state could predict the four knowledge types of the improved PDP among two groups. The participants’ control of the four knowledge types (degree of consciousness) gradually improved. Correspondingly, the brain areas in the resting-state positively related to the four knowledge types, gradually changed from the sensory and motor network to the somatic sensorimotor network, and then to the implicit learning network, and then to the consciousness network. The brain areas in the resting-state negatively related to the four knowledge types gradually changed from the consciousness network to the sensory and motor network. As SOA increased, the brain areas associated with almost all the four knowledge types changed. (3) The inhomogeneous hypothesis of the MET is best suited to interpret behavioral and neuroimaging data; it states that the same components among the four knowledge types are not homogeneous, and the same knowledge types are not homogeneous between the two SOA groups.

In this study, we explore the psychological mechanisms underlying the relation between college students’ post-traumatic growth and their entrepreneurial intentions in the post-COVID-19 era. Using the post-traumatic growth, entrepreneurial self-efficacy, prosocial tendency, and entrepreneurial intention scales, we tested 690 valid samples of Chinese undergraduates. The results revealed that post-traumatic growth of college students in the post-COVID-19 era will have a significant and positive effect on their entrepreneurial intentions. Additionally, the results indicated that students’ entrepreneurial self-efficacy and prosocial tendencies play a partial mediation role between post-traumatic growth and entrepreneurial intentions in the post-COVID-19 era and that there is a chain mediating effect between students’ entrepreneurial self-efficacy and prosocial tendencies. This study provides valuable insights into the influence of post-traumatic growth on entrepreneurial intentions among college students in the post-COVID-19 era and suggests that colleges and universities can improve students’ entrepreneurial intentions by adopting measures to foster their post-traumatic growth, entrepreneurial self-efficacy, and prosocial tendencies.