Antibiotic resistance in bacteria has become a great threat to global public health. Tigecycline is a next‐generation tetracycline that is the final line of defense against severe infections by pan‐drug‐resistant bacterial pathogens. Unfortunately, this last‐resort antibiotic has been challenged by the recent emergence of the mobile Tet(X) orthologs that can confer high‐level tigecycline resistance. As it is reviewed here, these novel tetracycline destructases represent a growing threat to the next‐generation tetracyclines, and a basic framework for understanding the molecular epidemiology and (...) resistance mechanisms of them is presented. However, further large‐scale epidemiological and functional studies are urgently needed to better understand the prevalence and dissemination of these newly discovered Tet(X) orthologs among Gram‐negative bacteria in both human and veterinary medicine. (shrink)

BackgroundCompassion fatigue is often associated with moral distress in the nursing practice among registered nurses. Moral resilience is an important ability to maintain, restore, or promote their...

The existing fuzzy rough set models all believe that the decision attribute divides the sample set into several “clear” decision classes, and this data processing method makes the model sensitive to noise information when conducting feature selection. To solve this problem, this paper proposes a robust fuzzy rough set model based on representative samples. Firstly, the fuzzy membership degree of the samples is defined to reflect its fuzziness and uncertainty, and RS-FRS model is constructed to reduce the influence of the (...) noise samples. RS-FRS model does not need to set parameters for the model in advance and can effectively reduce the complexity of the model and human intervention. On this basis, the related properties of RS-FRS model are studied, and the sample pair selection algorithm based on RS-FRS is used for feature selection. In this paper, RS-FRS is tested and analysed on the open 12 datasets. The experimental results show that RS-FRS model proposed can effectively select the most relevant features and has certain robustness to the noise information. The proposed model has a good applicability for data processing and can effectively improve the performance of feature selection. (shrink)

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved (...) in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed. (shrink)

本书从创造和思想两方面,勾勒出西方一段艺术审美的演进过程,并说明这一演进的主导轨迹。内容包括古典时期的艺术与哲学、多元文化下的艺术审美、艺术哲学的体系建构以及艺术走向现代的分流四部分。.

Due to the current COVID-19 pandemic, colleges and universities have implemented network teaching. E-learning engagement is the most important concern of educators and parents because this will directly affect student academic performance. Hence, this study focuses on students’ perceived family support and their e-learning engagement and analyses the effects of e-learning normative consciousness and behaviours and self-efficacy on the relationship between family support and e-learning engagement in college students. Prior to this study, the relationship between these variables was unknown. Four (...) structural equation models revealed the multiple mediating roles of e-learning normative consciousness and behaviours and self-efficacy in the relationship between family support and e-learning engagement. A total of 1317 college students (mean age = 19.51; 52.2% freshman) voluntarily participated in our study. The results showed that e-learning normative consciousness and behaviours and self-efficacy played significant and mediating roles between students’ perceived family support and their e-learning engagement. Specifically, these two individual variables fully mediated the relationship between students’ perceived family support and their e-learning engagement. The multiple mediation model showed that family members can increase family support of their children by creating a household environment conducive to learning, displaying positive emotions, demonstrating the capability to assist their children, advocating the significance of learning normative consciousness and behaviours and encouraging dedicated and efficient learning. The findings complement and extend the understanding of factors influencing student e-learning engagement. (shrink)

The relationship between children and their maternal uncles in contemporary Mosuo culture reveals a unique parenting mode in a matrilineal society. This study compared the responses of Mosuo and Han participants from questionnaires on the parent–child and maternal uncle–child relationship. More specifically, Study 1 used Inventory of Parent and Peer Attachment to assess the reactions of the two groups to the relationship between children and their mothers, fathers, and maternal uncles. The results show that while Han people display a higher (...) level of attachment toward their fathers than their maternal uncles, Mosuo people do not exhibit a significant difference in this aspect. Study 2 used a scenario-based method to compare how adults and teenagers perceive the rights and responsibilities of fathers/maternal uncles toward their children/nephews or nieces. The results show that Han adults attribute more rights and responsibilities to their own children than nephews/nieces, while their Mosuo counterparts have the reverse pattern and assign stronger responsibilities to their nephews/nieces than their own children. Both groups perceive the fathers to be the bearer of rights and responsibilities, although this perception was weaker among Mosuo. This paper concludes that in the Mosuo society, fathers have a relatively weak social role as a result of their unique matrilineal social structure. (shrink)

Protein redox reactions are one of the most basic and important biochemical actions. As amino acids are weak redox mediators, most protein redox functions are undertaken by protein cofactors, which include organic ligands and transition metal ions. Since both kinds of redox cofactors were available in the pre‐protein RNA world, it is challenging to explore which one was more involved in redox processes of primitive proteins? In this paper, using an examination of the redox cofactor usage of putative ancient proteins, (...) we infer that organic ligands participated more frequently than transition metals in redox reactions of primitive proteins, at least as protein cofactors. This is further supported by the relative abundance of amino acids in the primordial world. Supplementary material for this article can be found on the BioEssays website. BioEssays 30:766–771, 2008. © 2008 Wiley Periodicals, Inc. (shrink)

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the (...) development of the community-based Coronavirus Infectious Disease Ontology in early 2020. -/- As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. -/- CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications. (shrink)

Migraine is a chronic and idiopathic disorder leading to cognitive and affective problems. However, the neural basis of migraine without aura is still unclear. In this study, dynamic amplitude of low-frequency fluctuations analyses were performed in 21 patients with migraine without aura and 21 gender- and age-matched healthy controls to identify the voxel-level abnormal functional dynamics. Significantly decreased dALFF in the bilateral anterior insula, bilateral lateral orbitofrontal cortex, bilateral medial prefrontal cortex, bilateral anterior cingulate cortex, and left middle frontal cortex (...) were found in patients with migraine without aura. The dALFF values in the anterior cingulate cortex were negatively correlated with pain intensity, i.e., visual analog scale. Finally, support vector machine was used to classify patients with migraine without aura from healthy controls and achieved an accuracy of 83.33%, sensitivity of 90.48%, and specificity of 76.19%. Our findings provide the evidence that migraine influences the brain functional activity dynamics and reveal the neural basis for migraine, which could facilitate understanding the neuropathology of migraine and future treatment. (shrink)

This study explored the relationship among the emotional labor, psychological capital, and mental health of preschool teachers. A questionnaire survey was conducted on 411 preschool teachers in China. The results revealed the following: One emotional labor strategy had a significant negative effect on mental health, whereas two emotional labor strategies had significant positive effects. The psychological capital of preschool teachers had a complete mediation on the relationship between expression of naturally felt emotions and mental health and between the deep acting (...) and mental health. (shrink)

Articulated arm coordinate measuring machine is a specific robotic structural instrument, which uses D-H method for the purpose of kinematic modeling and error compensation. However, it is difficult for the existing error compensation models to describe various factors, which affects the accuracy of AACMM. In this paper, a modeling and error compensation method for AACMM is proposed based on BP Neural Networks. According to the available measurements, the poses of the AACMM are used as the input, and the coordinates of (...) the probe are used as the output of neural network. To avoid tedious training and improve the training efficiency and prediction accuracy, a data acquisition strategy is developed according to the actual measurement behavior in the joint space. A neural network model is proposed and analyzed by using the data generated via Monte-Carlo method in simulations. The structure and parameter settings of neural network are optimized to improve the prediction accuracy and training speed. Experimental studies have been conducted to verify the proposed algorithm with neural network compensation, which shows that 97% error of the AACMM can be eliminated after compensation. These experimental results have revealed the effectiveness of the proposed modeling and compensation method for AACMM. (shrink)

The aim of the study was to use an clustering analysis method to classify and identify native and foreign basketball players into similar groups based on game-related statistics; use the Pearson’s Chi-square test to identify the key clusters that affect whether a team enters the playoffs; and use the classification tree analysis to stimulate the prediction of team ability and the construction of the team roster. The sample consisted of 422 foreign players and 1,775 native players across 9 seasons from (...) 2011 to 2019. The clustering process allowed for the identification of nine native and six foreign player performance profiles. In addition, two clusters of native players and one cluster of foreign players were identified that had a significant impact on team ability. These results provide alternative references for basketball staff concerning the process of evaluating native and foreign player performance in the Chinese Basketball Association. (shrink)

To explore whether the generation of new protein folds could be linked to metallic cofactor recruitment, we identified the oldest examples of folds for manganese, iron, zinc, and copper proteins by analyzing their fold‐domain mapping patterns. We discovered that the generation of these folds was tightly coupled to corresponding metals. We found that the emerging order for these folds, i.e., manganese and iron protein folds appeared earlier than zinc and copper counterparts, coincides with the putative bioavailability of the corresponding metals (...) in the ancient anoxic ocean. Therefore, we conclude that metallic cofactors, like organic cofactors, play an evolutionary role in the formation of new protein folds. This link could be explained by the emergence of protein structures with novel folds that could fulfill the new protein functions introduced by the metallic cofactors. These findings not only have important implications for understanding the evolutionary mechanisms of protein architectures, but also provide a further interpretation for the evolutionary story of superoxide dismutases. (shrink)

ABSTRACT Leaders have been thought to play a vital role in influencing employees’ unethical behavior. However, what happens to leaders and followers in the aftermath of unethical conduct has received little attention in the literature. Drawing from the correspondent inference theory, we examine the conditions under which leaders attribute their followers’ unethical behavior to poor moral character and eventually assign them low performance ratings. Through a two-wave research design and data from 290 matched employee–leader dyads, we found that a leader (...) is more likely to infer that a follower who has engaged in unethical behavior is of poor moral character when the leader has a higher moral identity, and the leader will impose lower performance ratings on this follower when the leader prefers lower moral decoupling. (shrink)

BackgroundThe COVID-19 pandemic called for a new ethical climate in the designated hospitals and imposed challenges on care quality for anti-pandemic nurses. Less was known about whether hospital ethical climate and nurses’ ethical sensitivity were associated with care quality. This study examined the association between the perceived hospital ethical climate and self-evaluated quality of care for COVID-19 patients among anti-pandemic nurses, and explored the mediating role of ethical sensitivity in this relationship.MethodsA cross-sectional study was conducted through an online survey. A (...) total of 399 anti-pandemic nurses from ten designated hospitals in three provinces of China were recruited to fill out an online survey. Multiple linear regression analysis and a bootstrap test were used to examine the relationships between ethical climate, ethical sensitivity and care quality.ResultsNurses reported mean scores of 4.43 ± 0.577 (out of 5) for hospital ethical climate, 45.00 ± 7.085 (out of 54) for ethical sensitivity, and 5.35 ± 0.661 (out of 6) for self-evaluated care quality. After controlling for covariates, perceived hospital ethical climate was positively associated with self-evaluated care quality (direct effect = 0.710, 95% confidence interval [CI] 0.628, 0.792), and was partly mediated by ethical sensitivity (indirect effect = 0.078, 95% confidence interval [CI] 0.002, 0.145).ConclusionsChinese nurses who cared for COVID-19 patients perceived high levels of hospital ethical climate, ethical sensitivity, and self-evaluated care quality. Positive perceptions of hospital ethical climate were both directly associated with a higher level of self-evaluated care quality and indirectly associated, through the mediation effect of ethical sensitivity among anti-pandemic nurses. (shrink)

The COVID-19 pandemic has caused tremendous loss starting from early this year. This article aims to investigate the change of anxiety severity and prevalence among non-graduating undergraduate students in the new semester of online learning during COVID-19 in China and also to evaluate a machine learning model based on the XGBoost model. A total of 1172 non-graduating undergraduate students aged between 18 and 22 from 34 provincial-level administrative units and 260 cities in China were enrolled onto this study and asked (...) to fill in a sociodemographic questionnaire and the Self-Rating Anxiety Scale twice, respectively, during February 15 to 17, 2020, before the new semester started, and March 15 to 17, 2020, 1 month after the new semester based on online learning had started. SPSS 22.0 was used to conduct t-test and single factor analysis. XGBoost models were implemented to predict the anxiety level of students 1 month after the start of the new semester. There were 184 and 221 students who met the cut-off of 50 and were screened as positive for anxiety, respectively, in the two investigations. The mean SAS scores in the second test was significantly higher than those in the first test. Significant differences were also found among all males, females, and students majoring in arts and sciences between the two studies. The results also showed students from Hubei province, where most cases of COVID-19 were confirmed, had a higher percentage of participants meeting the cut-off of being anxious. This article applied machine learning to establish XGBoost models to successfully predict the anxiety level and changes of anxiety levels 4 weeks later based on the SAS scores of the students in the first test. It was concluded that, during COVID-19, Chinese non-graduating undergraduate students showed higher anxiety in the new semester based on online learning than before the new semester started. More students from Hubei province had a different level of anxiety than other provinces. Families, universities, and society as a whole should pay attention to the psychological health of non-graduating undergraduate students and take measures accordingly. It also confirmed that the XGBoost model had better prediction accuracy compared to the traditional multiple stepwise regression model on the anxiety status of university students. (shrink)

Instructional interactions, which includes student–student interaction, student–teacher interaction, and student–content interaction, are crucial factors affecting the learning outcomes in online education. The current study aims to explore the effects of instructional interactions on individuals’ learning outcomes based on the Interactive Equivalence Theory by conducting two empirical studies. In Study 1, we explored the direct relationships between instructional interactions and learning outcomes. A quasi-experimental design was used to manipulate the two groups of subjects, and the results show that not all of (...) the three types of interaction can significantly positively predict learning satisfaction, among which ST cannot significantly predict learning satisfaction. When the total amount of instructional interactions is constant, adjusting the relative level of the three types of instructional interactions can effectively improve the learning outcomes to some extent. We further probed into the mediating effects of task value and self-regulated learning on the relationships between instructional interactions and learning outcomes in Study 2. We conducted an online survey and collected 374 valid data. The results showed that task values mediated the relationship between SS and learning satisfaction. In addition, SC can not only directly affect learning satisfaction, but also affect it through task value and self-regulated learning respectively, or via chain mediations of both task value and self-regulated learning. Our findings enrich the previous instructional interactions research and provide reference for online education curriculum design. (shrink)

Brand rumors can harm brands’ image and bring significant impacts on customers’ decision-making and sharing behavior. Finding practical strategies for preventing the spread of brand rumors continues to be a challenge. Building on the social contagion theory, the current research enriches the discussion on understanding why people spread rumors and how to deal with the spreading of rumors. Sharing brand rumors is motivated by a variety of complex psychological reasons, but prior research didn’t adequately analyze the problem from a complexity (...) perspective. Therefore, using a sample of 416 interviewers within eight types of brand rumors, this study employs fuzzy-set qualitative comparative analysis to investigate the combination of rumor psychological communication motivations in brand activities and solutions to prevent the spread of brand rumors. The current study discoveries three and two first-level configurational solutions, respectively, that can promote positive and negative rumor spreading. To summarize, emotional stimulation is a key component in the spread of rumors; altruism and relationship management motivation can coexist at times; and untrusted rumors are disseminated through other motivation factors. Solutions to prevent rumors from spreading are also provided. Furthermore, the findings help to understand the psychology of configurational motivation and how it can help brands reduce the spread of brand rumors. Finally, these discoveries’ theoretical contributions and practical implications are presented. (shrink)

Publications by Chinese researchers in scientific journals have dramatically increased over the past decade; however, academic misconduct also becomes more prevalent in the country. The aim of this prospective study was to understand the perceptions of Chinese biomedical researchers towards academic misconduct and the trend from 2010 to 2015. A questionnaire comprising 10 questions was designed and then validated by ten biomedical researchers in China. In the years 2010 and 2015, respectively, the questionnaire was sent as a survey to biomedical (...) researchers at teaching hospitals, universities, and medical institutes in mainland China. Data were analyzed by the Chi squared test, one-way analysis of variance with the Tukey post hoc test, or Spearman’s rank correlation method, where appropriate. The overall response rates in 2010 and 2015 were 4.5% and 5.5%, respectively. Data from 15 participants in 2010 were invalid, and analysis was thus performed for 1263 participants. Among the participants, 54.7% thought that academic misconduct was serious-to-extremely serious, and 71.2% believed that the Chinese authorities paid no or little attention to the academic misconduct. Moreover, 70.2 and 65.2% of participants considered that the punishment for academic misconduct at the authority and institution levels, respectively, was not appropriate or severe enough. Inappropriate authorship and plagiarism were the most common forms of academic misconduct. The most important factor underlying academic misconduct was the academic assessment system, as judged by 50.7% of the participants. Participants estimated that 40.1% of published scientific articles were associated with some form of academic misconduct. Their perceptions towards academic misconduct had not significantly changed over the 5 years. Reform of the academic assessment system should be the fundamental approach to tackling this problem in China. (shrink)

Business Ethics: A European Review, EarlyView.

It has been demonstrated that the propagation of information and awareness regarding a disease can assist in containing the outbreak of epidemics. Previous models for this coevolving usually introduced the dependence between these two processes by setting a lower but time-independent infection rate for individuals with awareness. However, a realistic scenario can be more complicated, as individual vigilance and the adopted protective measures may depend on the extent of the discussion on the disease, whereas individuals may be irrational or lack (...) relevant knowledge, leading to improper measures being taken. These can introduce a time-varying dependence between epidemic dynamics and awareness prevalence and may weaken the effect of spreading awareness in containing a pandemic. To better understand this effect, we introduce a nonlinear dependence of the epidemic infection rate on awareness prevalence, focusing on the effect of different forms of dependence on the coevolving dynamics. We demonstrate that a positive correlation between vigilance and awareness prevalence can enhance the effect of information spreading in suppressing epidemics. However, this enhancement can be weakened if some individuals are irrational. Our results demonstrate the importance of rational behavior in the strategy of containing epidemics by propagation of disease information. (shrink)

Despite various studies examining intertemporal choice with hypothetical rewards due to problematic real reward delivery, there remains no substantial evidence on the effect of the incentives on the decision confidence and cognitive process in intertemporal choice and no comprehensive exploration on the loss domain. Hence, this study conducts an eye-tracking experiment to examine the effect of incentive approach and measure participants' decision confidence using a between-subject design in both gain and loss domains. Results replicated previous findings which show incentives do (...) not affect intertemporal choice in the gain domain. In contrast, in the loss domain, participants in the incentivized group were more likely to choose the larger-later options than those in the non-incentivized group. Furthermore, the decision confidence and the mean fixation duration differed between the incentivized and non-incentivized groups in both gain and loss domains. These findings allow for a better understanding of the effect of incentives on intertemporal choice and provide valuable information for the design of incentives in future intertemporal experiments. (shrink)

This study investigated the relationships between parental responsiveness, teaching responsiveness, and creativity, as well as the mechanism underlying these associations. We collected data from 584 Chinese college students via convenience sampling method and used self-report scales to measure their perceived parental responsiveness, teaching responsiveness, creative self-efficacy, and creativity. We employed structural equation modeling to examine the relationships among these variables and the mediation effect. The results revealed that both parental responsiveness and teaching responsiveness were positively related to student creativity. Moreover, (...) creative self-efficacy mediated the relationships of parental responsiveness, teaching responsiveness, and creativity. The findings highlight the significance of responsiveness from parents and teachers on student creativity and verify the potential mediating role of creative self-efficacy. These findings suggest that teachers and parents can foster creativity by providing warm and supportive responses to students’ creative needs. (shrink)

This study explored the effect of word knowledge facets on second language Chinese lexical inference by highlighting the moderating effect of language proficiency level and learners’ heritage status. L2 Chinese learners with a mixture of linguistic and cultural backgrounds completed a series of word-knowledge measurements as well as a lexical inferencing task. Through a moderated path model, the study demonstrated that word-general knowledge and word-specific knowledge contributed to L2 Chinese lexical inference. In addition, the study underlined the moderating effect of (...) heritage status on the correlation between word knowledge and lexical inference. Given the distinct patterns between heritage and non-heritage learners, morphological awareness may define the characteristics of reading profiles in the Chinese heritage learner population. (shrink)

Nowadays, the development of human society and daily life are inseparable from the power supply. Therefore, people also put forward higher requirements for the reliability of distribution network, but power companies can only passively deal with distribution network failures, which is a bottleneck for the improvement of distribution network reliability. The Internet of Things is the best solution for online equipment status monitoring and basic data sharing for large, widely distributed, relatively fixed, and large numbers of equipment. The construction of (...) the IoT for power distribution equipment faces many important problems, including the selection of networking, equipment selection, and interaction standards. When researching the implementation plan, research on the distribution of IoT market was carried out. Based on the grid, the idea of optimizing the investment selection plan of the power distribution using IoT was discussed, and a result verification model was established. After the completion of the theoretical part, a case study of medium-voltage distribution grid equipment management and medium-voltage distribution network equipment management based on the grid was carried out by taking a real enterprise application situation as an example. Realizing fault diagnosis of distribution network will not only provide decision support for operation and maintenance of distribution network for power companies, but also have great economic and social benefits. Aiming at the shortcomings of single data mining method in distribution network fault diagnosis, hybrid data mining method is proposed. First, rough set theory is used to reduce the original fault data and form a simplified rule set. Because of the non-linearity of distribution network fault and the strong learning ability, adaptability, and robustness of Bayesian network, Bayesian network can be used to classify distribution network faults. Therefore, a simplified fault diagnosis system is established in this paper, and its correctness is confirmed. Then, the learning and training are carried out by using Bayesian network to call the simplest rule set, which has the characteristics of short learning and training time and high diagnostic accuracy. (shrink)

Previous studies have reported abnormal amplitude of low-frequency fluctuation and regional homogeneity in patients with migraine without aura using resting-state functional magnetic resonance imaging. However, how whole brain functional connectivity pattern homogeneity and its corresponding functional connectivity changes in patients with migraine without aura is unknown. In the current study, we employed a recently developed whole brain functional connectivity homogeneity method to identify the voxel-wise changes of functional connectivity patterns in 21 patients with migraine without aura and 21 gender and (...) age matched healthy controls. Moreover, resting-state functional connectivity analysis was used to reveal the changes of corresponding functional connectivities. FcHo analyses identified significantly decreased FcHo values in the posterior cingulate cortex, thalamus, and left anterior insula in patients with migraine without aura compared to healthy controls. Functional connectivity analyses further found decreased functional connectivities between PCC and medial prefrontal cortex, between AI and anterior cingulate cortex, and between THA and left precentral gyrus. The functional connectivities between THA and PCG were negatively correlated with pain intensity. Our findings indicated that whole brain FcHo and connectivity abnormalities of these regions may be associated with functional impairments in pain processing in patients with migraine without aura. (shrink)