The information propagation of emergencies in social networks is often accompanied by the dissemination of the topic and emotion. As a virtual sensor of public emergencies, social networks have been widely used in data mining, knowledge discovery, and machine learning. From the perspective of network, this study aims to explore the topic and emotion propagation mechanism, as well as the interaction and communication relations of the public in social networks under four types of emergencies, including public health events, accidents and disasters, social security events, and natural disasters. Event topics were identified by Word2vec and K-means clustering. The biLSTM model was used to identify emotion in posts. The propagation maps of topic and emotion were presented visually on the network, and the synergistic relationship between topic and emotion propagation as well as the communication characteristics of multiple subjects were analyzed. The results show that there were similarities and differences in the propagation mechanism of topic and emotion in different types of emergencies. There was a positive correlation between topic and emotion of different types of users in social networks in emergencies. Users with a high level of topic influence were often accompanied by a high level of emotion appeal. With the development of the Internet, social networks based on social media have become the main channel for the public to share their daily life, express their views, and interact with each other. The breaking of the time and space restrictions of social media leads to the rapid spread of public emergencies, making social networks become the “virtual sensor” of various public emergencies . When a On the other hand, with the development of the economy and the transformation of society, social problems and contradictions around the world have become increasingly acute, which lead to all kinds of public emergencies from time to time. When a public emergency is formed, to reduce uncertainty, people tend to have a strong demand for information on the development of the event and policy response and try to obtain relevant information from social networks . HoweverSince the birth of the concept of Web2.0 in 2004, social media has not only opened up a new space for information exchange and opinion expression but also served as an important driving factor for social reform , which m(1)What are the commonalities and differences of different types of emergencies in the network propagation process of the topic and emotion?(2)What is the relationship between the topic and emotional propagation of different types of public emergencies in social networks?The development of social media technology has broken the limitation of media, space, and time, and the social network built through social media has deeply influenced society. However, the lack of applicable laws and regulations in social media platforms and the imperfection of management and organization systems make the current cyberspace full of disorder, distortion, and other negative characteristics. People use various media to spread the information they like or dislike, which makes people enjoy the pluralistic and open atmosphere of the information society, but also face the objective risks brought by the network public opinion. When public emergencies occur, the public tends to lack thinking about the facts in a short time and be carried away by irrational negative remarks, resulting in emotional excitement, a sharp increase in pressure, and magnified anxiety. At this time, the public tends to seek resonance in social networks, but under the effect of group polarization, it is easy to be bound by the majority of groups and go to extremes, endangering public safety and social stability. The characteristics of social media, such as unstructured, spontaneous, large user base, fast transmission speed, many irrational emotions, and group polarization, also increase the difficulty for the government to manage . TherefoTo solve the above questions, this study investigates the generation and propagation characteristics of topic and emotion content of multiple subjects in different public emergencies based on social network analysis, knowledge discovery, and deep learning approach, and constructs the topic and emotion propagation maps of different types of public emergencies in social networks.The rest of this paper is structured as follows. In In order to process large amounts of information to achieve the expected research results, machine learning algorithms (or pattern recognition and data mining ) are usuDeep learning has outstanding performance in various research fields, including related research based on social networks . With FaDeep learning also has outstanding performances in natural language processing (NLP), especially topic classification, emotion analysis, question answering, and language translation. For example, based on CNN, the malware system call sequences were modeled to classify malware . The worEmotion refers to people′s subjective feelings towards objective behaviors, while sentiment is the attitude, thought, or judgment caused by feeling. The sentiment is a further reflection of emotional polarization . At the Compared with traditional media, social media has an advantage in collecting and delivering messages. By using social media such as Twitter and Weibo, the public can publish, share and disseminate information in real-time ,36. ThisIn recent years, social networks based on social media platforms have been widely used, among which the monitoring of unexpected public emergencies is one of the most common applications . In thisThe frequency of public emergencies is increasing during the social transformation. The controversy of public emergencies is often accompanied by a variety of emotions . TherefoOn the other hand, the emotion under the public emergency evolution law of diffusion in social networks was well concerned. For example, some studies adopted the methods of time analysis and inferential statistical analysis and found that the sentiment evolution in social networks was consistent with the development of the events. Under different event topics and lifecycle, the sentiments presented different changes . A previTo sum up, the propagation mechanism of public emergencies in social networks has become a hot topic of academic attention. Some explorations have been made on the influencing factors of the propagation process, which provides a basis for this study to explore the topic and emotion propagation of public emergencies in social networks based on the deep learning method. At present, research on emergencies in social networks mostly emphasize the influence of government departments as the main body of information release, while the spreading mechanism of topic and emotion under different user types in social networks has not been highlighted. Existing studies mostly choose a single dimension of emergencies, with little consideration given to the differences in topic and emotion propagation of different types of emergencies in social networks. These are the directions to be explored in this study.The method of extracting valuable topics that can arouse public interest from big data is called topic recognition. Topic recognition is widely used in public opinion analysis, news lead tracking, business analysis, and other fields . ExistinWord2vec is a word embedding method proposed by Google in 2013, which is a shallow and two-layer neural network language model. Based on a given corpus, words can be transformed into word vectors more effectively through the optimized training model . ThroughThe Skip-gram model is mainly used to predict the context of the current word or sentence. The basic Skip-gram model is defined as Traditional content analysis methods are limited by human cost and other factors when faced with large-scale social media data, so computer-aided emotion analysis methods are widely used. Commonly used emotion analysis methods mainly include emotion computation based on emotion dictionary and classification algorithm based on machine learning technology ,74. The In related studies on emotion analysis using deep learning models, recurrent neural networks (RNNs) that are capable of processing sequence data such as text are the most common. In order to overcome problems such as gradient disappearance, gradient explosion, and short-term memory, researchers proposed the long short-term memory (LSTM) model . LSTM maThe emergence of LSTM solves the problems faced by traditional RNN, but LSTM adopts a front-to-back order in the processing of sequence data, ignoring the future characteristics of sequence data (through the backward state). Therefore, the bidirectional LSTM (biLSTM) model is proposed. Compared with the LSTM model, the biLSTM model combines the information in both forward and backward directions of the input sequence, so it has more advantages in short text emotion analysis . The strIn addition, the pre-training model can make use of massive unlabeled corpus data, which are widely used for a variety of natural language processing tasks. By fine-tuning the pre-training model, a better result of emotion classification can be achieved. Pre-training is generally divided into two steps. First, the model is trained with a large dataset; the next step is to transform the pre-training model according to different tasks and fine-tune the pre-training model with the dataset of this task.In this study, natural disasters, accidents and disasters, public health, and social security incidents were selected as examples. Python software was used to collect the microblog corpus published by users. After that, text content was filtered, stop words were removed and user types were classified. In terms of data analysis, we analyzed the propagation mechanism of topic and emotion in social networks when public emergencies occurred. The topics were identified through the Word2Vec and K-means clustering method. The emotion of posts was classified by the bidirectional long and short-term memory mode. Finally, we explored the law of the co-evolution of topic and emotion in social networks through the concepts of topic out-degree and emotion out-degree, and used the topic and emotion propagation maps to visualize. The research framework is shown in This paper took public emergencies as the research object. According to the types of emergencies, public emergencies can be divided into four types: natural disasters, accidents and disasters, public health events, and social security events. In order to compare the propagation mechanism of different types of emergencies in social networks. This study selected one case of each type that happened in recent years, including the fire in Liangshan, Sichuan Province , the collapse of the hotel isolated from the epidemic in Quanzhou (accident disaster), the epidemic of the Diamond Princess cruise ship  and the hostage-taking of students in Kunming . Sina Weibo platform was selected as the data source to gather emergencies related text data.Sina Weibo is one of the most popular social media platforms in China. According to Weibo′s financial report for the fourth quarter of 2020, the Weibo platform had 221 million monthly active users and 225 million daily active users in December 2020, making it one of the most widely used social media platforms in China. Through the use of Weibo, users can thumb up, comment, and forward any news or event, and build a huge social network through interaction in the social media platform. The four types of public emergencies selected have all become hot topics in Weibo, attracting the attention of a large number of users. Through the interaction and discussion among users, a large number of event topics, emotion data have been generated. Based on this, we gathered the emergency-related information by limiting the period and searching keywords. Each post included the content, the thumb up, comment, forwarding, as well as the publisher′s personal information.After the event-related text data were obtained, the data need to be preprocessed. The pre-processing methods adopted in this study are as follows. Firstly, regular expressions were used to filter non-text contents in text data, such as punctuation marks, HTML tags, etc. Secondly, since there was no space between Chinese statements, the study uses Jieba word segmentation to carry out word segmentation processing, so as to convert them into word vectors later. Finally, the Chinese stop word list provided by HIT was used to remove meaningless words. In addition, Sina Weibo users have multiple authentication types that indicate the user′s status, role, or affiliation. Considering the difference in status and influence of different types of users, this paper divided the user types into five categories according to the authentication type field of user information: ordinary users, celebrities, government, institutions, enterprises, and media.In this study, we used Word2vec and K-means to cluster the topic of various types of public emergencies in social networks. Firstly, in order to reduce the interference of useless information and noise in the Weibo text data, the TF-IDF method was used to calculate the importance of each word in each microblog file for the document representation. The top 20 words in TF-IDF weight are extracted from the largest to the smallest as the keyword representation of the microblog file. Then, the Skip-gram model was used to convert the unstructured microblog text into a computable and structured word vector. With the help of Gensim toolkit of Python language, the tokenized words are transformed into a 100-dimensional word vector. After that, for each public emergency, the K-means clustering method was used to cluster word vectors into topics. Each topic was represented by a series of keywords, which were further summarized into topic descriptions. Considering the influence of K value selection on the results, this study selected appropriate K values for different emergencies according to work requirements and repeated practice modifications.NLP&CC2013 and NLP&CC2014 datasets were used for Weibo sentiment classification task for the International Conference on Natural Language Processing and Chinese Computing, which has been widely used in the training and evaluation of Chinese sentiment classification models in recent years ,80. BecaIn order to improve the performance, as well as the generalization ability on unfamiliar datasets of the model, the pre-train model of microblog was established before the emotion classification model was trained . TherefoBased on the obtained data, Gephi software was used to construct the propagation maps of topic and emotion in social networks. In the construction of the topic and emotion propagation maps, the study defined a single Weibo user who forwards relevant information on the Weibo platform when an unexpected public event occurred as a “node”. The forwarding relationship between any two Weibo users in social networks in the transmission process was set as an “edge”. The structural attributes of forwarding networks related to different types of public emergencies were presented through network density, vector centrality, clustering coefficient, and other indicators.In order to further explore the evolution mechanism of topic and emotion in social networks, researchers defined the influence of topic and emotion in social networks as topic out-degree and emotion out-degree, respectively, based on existing studies. Among them, the topic out-degree was explained as the proportion of the same type of topic among all the nodes extending outward from the node in social networks built on the forwarding relationships. The emotion out-degree was interpreted as the proportion of the same type of emotion among all the nodes extending outward from the node in the social network formed by the construction of forwarding relationships . The forThe four types of public emergencies selected in this paper had all caused great repercussions in cyberspace and attracted the attention of the public. Internet users provided us with a wealth of topic and emotion data by posting, commenting, and forwarding on social media platforms. In this study, the forest fire in Liangshan, Sichuan Province, which happened on 30 March 2019, was selected as a natural disaster case. The accident occurred in Muli County, Liangshan Prefecture, Sichuan Province. The sudden forest fire caused a total of 31 deaths, of which 27 were local firefighters; The collapse of the quarantine hotel in Quanzhou City, Fujian Province on 7 March 2020, was selected as the accident disaster case. A total of 71 people were trapped at the time of the collapse, most of which were people who had been under quarantine observation in the hotel during the epidemic period. After the rescue, 42 people were finally rescued; as public health care, we selected the outbreak on the Diamond Princess ship on 1 February 2020. Some of the passengers on the Diamond Princess ship with more than 3000 people on board were detected to have COVID-19 and spread on the ship; the case of hostage-taking in Kunming, Yunnan Province on 22 January 2021, was selected as a social security case. A man with a knife wounded seven people at the gate of a local middle school and then took a student hostage. These incidents had been widely discussed on social media since their occurrence. By searching event hashtags, we found relevant discussions of events in social media, and collected the interactions of different types of emergencies in social networks under the condition of limiting the active time of the events, to obtain the microblog entries and forwarding numbers related to the events. The number of microblog entries and the Forwarding relationship of each event is shown in In the visualization of distribution and propagation, it was concerning that too many users participated in discussion and interaction when public emergencies occurred, and different types of public emergency datasets had differences in text quantity and spatial distribution. We selected different criteria to screen the number of nodes that constitute the spectrum for different types of public emergencies. For example, in the case of the natural disaster, the study selected users whose microblog entries were forwarded reached four times or more as nodes and then constructed the propagation maps of related topics and emotions in social networks when the natural disaster occurred. The specific filtering criteria is shown in It can be seen from Based on the obtained text data, we used Gephi software to build the propagation maps of event-related topics in social networks when different types of public emergencies occurred. In the construction process of the graph, nodes, and edges needed to be arranged by algorithms to meet the needs of the rationality of graph requirements and visual recognition. Different types of algorithms correspond to different layout methods in Gephi. According to the content needs, we chose to use the Fruchterman Reingold algorithm to layout and set the layout attributes, and finally constructed the propagation maps of the topics. The propagation maps of four different types of public emergency event-related topics in social networks were shown in Through the observation of the diffusion process of related topics in social networks after the occurrence of different types of public emergencies, we found that the most prominent topic category in the natural disaster event was the memory and tribute to fire heroes, followed by the related topic of condemning the netizens who insulted firefighters, which also attracted the public′s attention on social networks. When the accident happened, the shock of the collapse and the search and rescue at the Quanzhou Hotel became a major topic of public attention on social media. When the public health event occurred, the type of topic that gets the most public attention on social networks was the confirmation of COVID-19 infection among ship travelers. When the social security event occurred, the public′s interaction in social networks mainly revolved around the condemnation of the prisoners, sympathy for the abducted children, and the police kneeling. Secondly, the denial of the rumors by the families of the hostages had also aroused wide discussion among users in social networks. This also confirms that when public emergencies occurred, users in social networks paid the most attention to the specific information related to the event and the relevant situation involving the main characters. The relevant findings have guiding significance for public emergency management in case of emergency.In this study, the post text of different types of public emergencies in social media was collected, and the experimental text data were preprocessed based on emotion labeling of the training set data. After the cleaning, the text data were converted into word vectors by the Skip-gram model, and the emotions contained in the input vectors were classified by Bidirectional Long and Short-Term Memory model. The emotions can be divided into seven categories, which are “Like”, “Disgust”, “Surprise”, “Happiness”, “Fear”, “Sadness”, and “Anger”. Similarly, Gephi software was used to generate the emotion propagation maps in social networks when different types of public emergencies occurred, and the Fruchterman Reingold algorithm was used for layout. The emotion maps are shown in On the other hand, by mapping the evolution of emotions in social networks, we also found differences in user types when different types of public emergencies occurred. As can be seen from In the research design, we defined the topic out-degree and emotion out-degree of nodes as the influence of topic and emotion in social networks. Furthermore, the diffusion mechanism of the topic and emotion of public emergencies in social networks was further analyzed. Considering that there were a large number of nodes in social networks when public emergencies occurred, we selected the top 30 core nodes in the ranking of node out-degree for display. The horizontal and vertical coordinates represented the topic out-degree and emotion out-degree, respectively. The node color represented the user type of the node. Through the analysis of the topic out-degree and emotion out-degree of the core nodes, we could not only distinguish the differences in the influence of different topics and emotions, but it can also analyze the differences in the influence of different user types on the dissemination of topics and emotions. Therefore, we could further study the diffusion mechanism of topics and emotions in social networks when public emergencies occurred.Through the calculation of the topic out-degree, we also found that when various types of public emergencies occurred, the influence of the topic types of core nodes in social networks was different. In the natural disaster event, topic 2 (mourning and honoring the hero of firefighting) attracted the most attention, and the tribute to the firefighting hero became the focus of transmission in social networks. When the accident occurred, the topic types that attracted the most attention in social networks were topic 5 (pray for the safety of the affected people) and topic 6 (discussion on the cost of quarantine), respectively, which contained the public′s blessing and concern for the trapped people. When the public health event occurred, network users were most eager to discuss topic 6 (confirmed situation of cruise ship pneumonia) related to the event, and the understanding of the specific situation of the emergency became the focus of the spread of the topic in social networks. When the social security event occurred, topic 4 (police officers knelt on the ground) and topic 6 (relatives of hostages held in Kunming deny rumors) attracted the public′s attention most and aroused wide discussion.By calculating the topic out-degree and emotion out-degree, we further explored the diffusion mechanism of topic and emotion in social networks. It was found that, although the types of public emergencies selected were different, there was something in common between topics and emotions in the propagation of social networks when emergencies occurred. In the topic propagation, we found that the topic types that the public paid the most attention to in social networks focused on the understanding of the event situation and the rescuer and the victim when the event happened. In the emotion contagion, we found that when public emergencies occurred, the public′s overall emotion types in social networks were mainly negative emotions. However, positive emotions would also be generated due to the excellent qualities of the event-related objects in public emergencies. The bubbles in each figure are mainly located at the lower right of the figure, which indicates that the out-degree of topic was often greater than the out-degree of emotion. The topic information was more easily transmitted than the emotion in public emergencies.In this paper, we constructed the diffusion maps of related topics and emotions in social networks when different types of public emergencies occurred using topic recognition and emotion analysis. Through the calculation of topic out-degree and emotion out-degree, the topical influence and emotion contagion mechanism of the core nodes in social networks constructed by forwarding relationships were explored when an emergency occurred. It was of great significance for us to understand the propagation mechanism of public emergencies in social networks, maintained network security, and realized emergency management. At the end of this study, the paired sample t-test was used to test the significance of the mean differences of topic out-degree and emotion out-degree in different types of emergencies based on excluding isolated nodes. In addition, we used the method of correlation test to further explore whether the topic and emotion of different user types were related to each other in the evolution trend of social networks when public emergencies occurred.Firstly, the paired sample t-test was used to test whether there was a significant difference in the mean value of the topic exposure and emotion exposure when different types of public emergencies occurred. When there was a significant difference between the mean values, it proved that topic and emotion did not converge in the process of propagation and had their propagation characteristics. When there was no significant difference, topic and emotion had a more consistent evolution mechanism in the process of propagation. The test results are shown in Secondly, we tested the correlation between topic out-degree and emotion out-degree when different types of emergencies occurred, to explore the relationship between topic and emotion in the propagation process of social networks. The test results are shown in Finally, we divided users in social media into different types and compared the correlation degree of different types of users in terms of topic and emotion and explored the differences of topic diffusion and emotion contagion among different types of users when different types of public emergencies occurred. The test results are shown in We took different types of public emergencies as research objects and used social networks as a social sensor when public emergencies occurred. In addition, topic recognition and emotion analysis were adopted to explore the propagation mechanism of event-related topics and emotions in social networks when public emergencies occurred. Finally, visualization software was used to construct the propagation maps of the topic and emotion. To realize the recognition and extraction of relevant topics contained in text data, we first searched event keywords in social media in a limited period to obtain relevant data information and preprocessed the text data. Second, the text data were transformed into word vectors by the Skip-gram model. Finally, the K-means clustering method was used to realize the recognition of topic features and obtain topic feature words. To classify the emotions contained in textual data, we used a variant of the bidirectional long short-term memory (biLSTM) network to classify emotions into seven types based on training datasets, such as anger, and sadness.For research question 1, on the one hand, this study found the commonality among different emergencies in the topic and emotion communication. For the topic, rescue, accountability, and mourning were common topics in emergencies. For emotions, negative emotions, such as sadness and nausea, were more likely to spread in emergencies. On the other hand, this study found diffusive differences in topic and emotion of various types of emergencies. Natural disaster events involve the relationship between human beings and nature, and the conflict involved in the events was relatively single, which was easy to trigger the public to pay tribute to the rescuers. Public health events were prone to panic and heartbreak due to their potential harmfulness, while they were prone to anger over the topic of inadequate prevention and management. Since accidents and disasters reflect social contradictions and other real social problems, their discussions focused on the central node, which was more likely to lead to group polarization. Discussion of social security incidents was fragmented, as the media and the government may have played down the issue in order to reduce panic.For research question 2, this study found that the topic and emotion propagated simultaneously. Topic information diffused more easily than emotion. The collaborative diffusion of topic and emotion among releasing subjects was different. The topic–emotion collaborative diffusion relationship of media’s topic and emotion was relatively poor. The topic-emotion collaborative diffusion relationship of ordinary users and celebrities was more synchronized. However, this study also found that the media, government had advantages in the scale of information diffusion. Thus, it can be inferred that the multi-level diffusion relationship of the public emergencies. The information of the emergency event receives wide attention through the amplifier function of media and government social media accounts, and then celebrities and ordinary users as participants conduct close topic and emotion communication.The findings of this study have some practical significance for emergency management. Firstly, according to the topic and emotion characteristics of emergencies, the emergency response department can formulate emergency plan according to the public opinion topic and emotion type that may appear in various types of emergencies. For example, coverage and recognition of the heroism of aid workers can be used to reduce public discontent and stabilize social order. Then, relevant departments should pay attention to the differences in the emotional diffusion ability of different nodes. When dealing with public opinions about events, emergency management departments should take differentiated measures, pay attention to the topical content and factual information revealed by the media and information released by departments, and guard against the abnormal guidance of celebrities’ opinions on public attention and emotion.As an exploratory study, this study has some limitations. First of all, this study only selected a single event case as a representative under various categories. The conclusions drawn by this study need to be verified on a larger event case set. Secondly, the field of natural language processing is developing rapidly, and the accuracy level of the topic clustering and emotion mining methods used in this study still needs to be further improved. Therefore, further research can expand the case event data and integrate time, geographical location, and other social media information to explore the co-evolution mechanism of the topic-emotion.


We present this case series exploring the complementary role of coronary computed tomography angiography (CCTA) to SPECT myocardial perfusion imaging (MPI) in the detection of myocardial necrosis.A cardiac hybrid imaging database search identified 144 patients with a previous history of ST-segment elevation myocardial infarction treated with coronary revascularization. CCTA and MPI scans were evaluated to determine whether CCTA had an added value to MPI in detecting myocardial necrosis.Five patients with patent stents and/or bypass grafts and both fixed perfusion defects on MPI and sub-endocardial hypo-perfusion on CCTA were identified. The extent and location of the perfusion defects were closely correlated between the CCTA and SPECT MPI images.In this series, CCTA and SPECT MPI were found to play a complementary role in the assessment of fixed perfusion defect, with CCTA adding specificity to the diagnosis of myocardial necrosis. Fixed perfusion defect (FPD) is a perfusion abnormality that is detected on both rest and stress SPECT MPI scans of the identical location, size and severity ) in the period between January 2014 and January 2018. All registry patients signed consents to be imaged into a registry to be imaged with CCTA and rest/stress SPECT-MPI and agreed to subsequent follow-up. This registry was approved by the local ethical committee.A two-day rest/stress protocol with Tc99m Sestamibi was employed for all patients. SPECT MPI imaging was performed on a cadmium–zinc–telluride solid-state detector (CZT) gamma camera with CT attenuation correction. The rest SPECT-MPI study and the CCTA scan were done on the same day. The stress SPECT MPI scan was performed the following day. Physically capable patients were stressed on the treadmill, while pharmacologic stress with dipyridamole ± exercise was performed in patients with limited exercise capacity.CCTA was performed after oral pre-medication with a goal of reducing the heart rate to less than 60 beats per minute. A 64-slice CT scanner was used for the CCTA within a few hours of the rest-SPECT scan. A timing bolus technique was employed to determine the delay time used to trigger the CCTA acquisition. Late-enhancement CT imaging was not performed as part of this protocol.N = 144) with a history of ST-segment elevation myocardial infarction (STEMI) who underwent revascularization with either percutaneous coronary intervention (PCI) or coronary artery bypass surgery were reviewed. From that subgroup, we report five patients with both FPD on SPECT-MPI scans and hypo-enhancement on CCTA scans, Figs. A subgroup of patients N = 44 with aA 66-year-old male with history of inferior STEMI treated with PCI to the right coronary artery. Echocardiography showed LVEF of 60% with no regional wall motion abnormalities. Six years later MPI Fig. A, B showA 78-year-old female with history of anterior STEMI treated with PCI to the left anterior descending artery (LAD). Echocardiography showed LVEF of 50% with mild hypo-kinesis of the anterior wall. Two years later MPI Fig. A, B showA 67-year-old male with history of anterior STEMI treated with PCI to LAD. Echocardiography showed LVEF of 30% with akinetic anterior, anterior-septum and apical segments. Four years later MPI  to the LAD, and PCI to RCA]. Echocardiography showed LVEF of 42% with hypo-kinesis of the anterior-septum, apical anterior wall segments and the apex. MPI  and non-stented coronary artery segments.In this report, we illustrate that CCTA is a unique imaging modality, providing both anatomical and perfusion details in patients with previous revascularization. In this dataset of patients with a history of STEMI and patent stents and grafts, FPD on SPECT MPI and subendocardial hypoperfusion on CCTA were found to be largely congruent. The CCTA findings increased the specificity of the SPECT MPI findings for myocardial necrosis as opposed to attenuation artifact or hibernating/viable myocardium. The utilization of a combined hybrid cardiac assessment allowed for a more definitive and comprehensive cardiac assessment. However, our findings cannot be generalized to patients with FPDs and severe coronary artery stenosis, as the hypo-enhancement with CCTA might result from resting ischemia and hibernation. Although promising, further studies enrolling patients without previous revascularization and comparing hypo-enhancement with CCTA with other cardiac viability imaging modalities such as cardiac MRI and FDG-PET are warranted.


Polycaprolactone (PCL) is a well-known FDA approved biomaterial for tissue engineering. However, its hydrophobic properties limit its use for skin wound healing which makes its functionalization necessary. In this work, we present the fabrication and evaluation of PCL nanofibers by the electrospinning technique, as well as PCL functionalized with 6-deoxy-6-amino-β-cyclodextrin (aminated nanofibers). Afterwards, epithelial growth factor (EGF) was anchored onto hydrophilic PCL/deoxy-6-amino-β-cyclodextrin. The characterization of the three electrospun fibers was made by means of field emission scanning electron microscopy (FESEM), Fourier transform infrared spectroscopy-attenuated total reflectance (FTIR-ATR); Confocal-Raman Spectroscopy were used for elucidated the chemical structure, the hydrophilicity was determined by Contact Angle (CA). In vitro cell proliferation test was made by seeding embryonic fibroblast cell line (3T3) onto the electrospun mats and in vivo studies in a murine model were conducted to prove its effectivity as skin wound healing material. The in vitro studies showed that aminated nanofibers without and with EGF had 100 and 150% more cell proliferation of 3T3 cells against the PCL alone, respectively. In vivo results showed that skin wound healing in a murine model was accelerated by the incorporation of the EGF. In addition, the EGF had favorable effects in epidermal cell proliferation. The study demonstrates that a protein of high biological interest like EGF can be attached covalently to the surface of a synthetic material enriched with amino groups. This kind of biomaterial has a great potential for applications in skin regeneration and wound healing. It is of them ,5,6. All of them . On the  of them ,9,10.Some strategies which search a synergistic effect on their properties include the addition of biological interest molecules by mixing different materials with or without covalent bonds ,10,11,12After an injury, several intracellular and intercellular processes should be activated and coordinated to restore tissue integrity and homeostasis where a long list of regulatory biomolecules are involved. Peptide growth factors are key molecules in re-epithelialization, the epithelial growth factor (EGF) family regulates re-epithelialization and wound repair. EGF has been encapsulated in different kind of polymers and then applied directly around the lesion to deliver it. However, EGF tends to a burst release with the need for search new strategies and systems that would incorporate and release EGF with good results in skin wound healing .In this context, we present the physicochemical characterization, as well the in vitro and in vivo wound repair evaluation of the electrospun nanofibers made with inclusion complex between PCL and 6-deoxy-6-amino-β-cyclodextrin (aminated nanofibers) which was incorporated in order to provide sites to anchor the EGF, this will reinforce the evaluation reported in our previous work . This maβ-CD-NH2 was obtained in agreement with the procedures of Yoshinori Kawaguchi et al. [The aminated nanofibers were prepared in accordance with a previous work . The usei et al.  and Jiahi et al. . Poly(e-w/v). The solution was heated in an oil bath until 50 °C. Once the temperature was reached, a solution of β-CD-NH2 in DMF with concentration of 0.833% (w/v) was added dropwise and stirred for 2 h. Then the mixture was let to cool down at room temperature and the acetone was evaporated overnight under slowly stirred. The uncomplexed β-CD-NH2 (6-deoxy-6-amino-β-cyclodextrin) was removed by washing the mixture several times, then it was dried at 37 °C under reduced pressure of 25 in Hg. Afterwards, the PCL with β-CD-NH2 was electrospun [A PCLwas used to prepare a solution with acetone at concentration of 1.66%  glutaraldehyde solution to activate the surface by the conjugation of glutaraldehyde with the amino groups of the material, it was put in a shaker for 1 h at room temperature. Afterwards, it was washed with phosphate solution to remove the unattached glutaraldehyde, then, it was dipped overnight into an EGF solution (10 µg/mL) at 4 °C under stirring. The final concentration was determined by UV-Vis spectroscopy and the grafted protein-material was quantified by absorbance difference between the initial contact protein concentration and the final protein concentration [The epithelial growth factor was covalently attached following an immobilization technique, using glutaraldehyde on amine groups of nanofibers ,20. Initntration . Aminatentration ,23,24,25−1 range with a resolution of 4 cm−1, 32 repetitive scans were automatically added for each measurement Ge crystal was used for the ATR mode. The wettability of the materials was evaluated by measuring in Drop Shape Analizer-DSA30 (Krüss) using a physiological solution.The characterization of the electrospun materials was made by means of Field Emission Scanning Electron Microscopy . The EGF distribution on the nanofibers was observed by means of Confocal Raman Microscopy  with an Olympus optical setup and 542 nm laser, a spectral scan was carried out allowing to create an image with the discrimination of the representative signals, as well as a composite image that allows to see the distribution of both signals ,27. Furt2. Moreover, to prevent contamination penicillin/streptomycin (1%) was added, the culture media were changed every 48 h. After rinsing with a PBS it was incubated with a 0.05% trypsin-EDTA solution. The activity of the trypsin was terminated after 1 to 2 min by the addition of 5 mL of complete growth medium. The mixture was centrifuge for a few minutes and the supernatant discarded. The cells were suspended in a fresh medium and then seeded into culture flasks for further propagation and subsequent passages. Cells from 2nd to 4th passages were seeded on the nanofibers with and without EGF in order to analyze their growth and proliferation for 14 days. Cell viability was measured according to Mosmann [2 incubator for 1 h. Afterwards, formazan crystals were dissolved in 100 μL of DMSO. The reduction of MTT was quantified using a microplate reader  by measuring the absorbance at 570 nm [A is the absorbance value of the control group and B is the absorbance value of nanofiber tested.Biocompatibility of “Aminated nanofibers with/without EGF” was measured using the methodology of MTT assays . The mou Mosmann  using MTt 570 nm . Viabili2 incubator for a period of 3, 7, 10, and 14 days. The cells were rinsed with PBS and incubated with 0.05% trypsin-EDTA at 37 °C in a humidified atmosphere with 5% CO2. After 1 to 2 min the activity of the trypsin enzyme was terminated by the addition of complete growth medium and then centrifuged for 5 min at 3000 rpm and the supernatant threw-away. The cells were suspended in 1 mL of fresh medium followed by taking 20 μL of it and mixed with 20 μL of Trypan blue; 10 μL of the mix were placed in Neubauer camera and counted in the 4 quadrants. The total number of cells in 1 mL was calculate by the following formula [N, FD, 10,000, and 4 are value cells in the fourth regions, dilution factor and correction factor, and the observed region number, respectively. Statistical analysis of these results was executed by the PRISMA statistical program.Cell proliferation was measured by place, in a 12-well plate, round pieces of the material with a diameter of 1.5 cm previously disinfected with UV light for 30 min. As control, it was used al tissue culture plate. 3000 cells per well were seeded for and incubated at 37 °C in a CO formula (2)proliIn vivo evaluation was made using a Murine model. The murine specimens were anesthetized with isoflurane and the dorsal area was shaved. Circular wounds of 1 cm in diameter were produced using a sterile skin biopsy punch, the wounds were digitally photographed. Then, before to be applied the materials (aminated nanofibers with and without EGF) were sterilized for 30 min in a UV lamp. The animals were taken care of and monitored for 14 days receiving a regular diet ,33,34,3517 amine groups per cm2. The number of amine groups on the surface of the aminated nanofibers was in the range of the obtained values by other works [The grafted electrospun materials with proteins have been reported by the glyceraldehyde junk reaction, using as base to graft aminated surfaces. In this sense, the amine groups on the surface of the aminated nanofibers were quantified in order to determine the capacity to attach the epithelial growth factor. The quantification was made by ninhydrin method  using ther works . The hig2 was obtained, this value corresponds to 2.67 × 1014 protein molecules grafted on the surface. The spectroscopic characterization of the materials worked was made by infrared spectroscopy. In −1 for the started materials, inclusion complex before and after the attachment of the EGF is shown.The epithelial growth factor (EGF) was anchored onto the aminated nanofibers mats by the immersion of the fibers in an EGF solution. The grafted protein was quantified by absorbance difference between the initial contact protein concentration and the final protein concentration. An average grafted value of 0.02 mg per cm−1 corresponding at amine-amide and hydroxyl groups, also CH2 stretching bands (2900–2800 cm−1); however, in aminocyclodextrin the amine group bending band is observed around 1590 cm−1, meanwhile the amide bands were observed to less wavenumber and amide carbonyl group and carboxyl group are showed at 1700 cm−1 [−1 due to the abundant carbonyl groups in the structure of the PCL, also the C-O and C-C bonds stretching band (1240 cm−1) of PCL chain are exhibited. In the structure with EGF the IR spectra showed the characteristic bands of amide groups at 1644 and 1514 cm−1, which are attributed to the grafted protein in the material indicating the presence of the EGF in the material [−1 is assigned to both a random coil and α-helix conformation of the protein, since the both materials contains analogous nitrogenated groups (amine and amide), related IR bands were observed from these groups in same wavenumber range (1590–1510 cm−1). However, it has been reported the vibrational mode of amide II from in-plane N-H bending appeared at lowest wavenumber than the primary amine N-H bending. In this case, it corresponds to the primary amine group of aminocyclodextrin [−1) increases its intensity due to the EGF attached. These similitudes on the IR signals, Raman Spectroscopy was used to complement the IR results and let us confirm the presence of EGF anchored by amide bond.Infrared spectrum from starter materials revealed similar bands, the both compounds, aminocyclodextrin and EGF showed broad band around 3500 cm700 cm−1 . The amimaterial ,40,41. Todextrin . The two−1) attributed to the peptide bonds of proteins. However, the aminated nanofibers without EGF did not show this band [−1 is displayed in the nanofibers with EGF and the same band is exhibited by EGF pure molecule spectra. Moreover, the band assigned to amine group (1606 cm−1) in aminated nanofibers without EGF [The vibrational spectroscopic characterization of aminated nanofibers was continued by Raman spectroscopy. The results  showed ihis band . In addihout EGF  decrease−1 (highlighted in red) is attributed to the EGF, the CH2 stretching band at 2857 cm−1 (highlighted in blue) highlighted to generate a complete image of the nanofibers which allowed us to correlate the position of the EGF across the nanofibers. The EGF distribution in the nanofibers is observed when both CRS images are spliced, causing the appearance of a magenta color due to the combination of red and blue. These images evidence that amine groups and in consequence the EGF are both well distributed along the PCL fibers.Complementarily, the aminated nanofibers with EGF were studied by confocal Raman spectroscopy (CRS) . CRS col2 in 5.56 s. These results indicated that the aminated nanofibers with EGF resulting highly hydrophilic. This property is an important factor for the adhesion and attachment of cells and proteins. This property is an indicative of the possible biocompatibility of the material, this is in agreement with other works [In er works .Additionally, an EGF release test without lipases and without amylases was carried out to confirm that the EFG is grafted on the surface of the nanofibers. The aminated nanofibers with EGF were immersed in phosphate buffer solution at pH of 7 and 0.1 M concentration, the absorbance was measured at 280 nm from 0 to 14 days. The results did not show an EGF release under experimental conditions confirming the EGF is grafted to surface.The biocompatibility of the aminated nanofibers with EGF was evaluated and compared with aminated nanofibers by MTT method. In The cell proliferation on the material was followed until day 14 with a constant increase of cell population. At the end of day 14, the cell population increased around four and five times, for aminated nanofibers and the aminated nanofibers with EGF material, respectively. These results agree with the proliferation step in the wound healing process. The increase in the cell population is attributed to the amine groups and EGF on the nanofibers surface improving the biocompatibility of the PCL.The obtained results suggest that the aminated nanofibers with and without EGF can present a good biocompatibility for wound healing due to the good adhesion, cell growth, and proliferation. The fibroblasts adhesion and proliferation on the nanofibers were followed by optical and electronic microscopy (SEM) during its culture assay as can be seen in The morphology and in vitro cytocompatibility on aminated nanofibers and aminated nanofibers with EGF were evaluated by FESEM. The growth of 3T3 cell line on the nanofibrous mats during the culture period was continued and observed on surface of the nanofibers in agreement with previously reported for other electrospun scaffolds . MoreoveIn order to evaluate these mats for wound healing, wounds of 1 cm in diameter were created by circular excision on the dermis and epidermis in the back of murine specimens. They were daily evaluated for 14 days and the analysis was made by triplicate. The observation periods were chosen according to the in vitro cell proliferation and cells population counts, using an untreated rat as control. Additionally, the wound healing was determined by wound area reduction and reported by healing percentage (Equation (2)), the results are shown on The in vivo results are in agreement with the in vitro study, which exhibited the best cell proliferation on the aminated nanofibers with EGF, followed by the aminated nanofibers without EGF. The murine accepted the aminated nanofibers with EGF without any complication, there was no loss of weight, neither macroscopic signs of inflammation or reddening of the tissue, the implant did not present fibrosis at all. The aminated nanofibers with EGF presented an accelerated healing compared with aminated nanofibers and the control.14 molecules per square centimeter. The in vitro assay showed that the aminated nanofibers and the aminated nanofibers with EGF improved their biocompatibility in comparison with only PCL nanofibers. In vivo tests showed that aminated nanofibers with EGF can accelerate the wound healing process in comparison with the others. This kind of biomaterials have the potential to be applied in wound healing, successfully.Biomaterial for skin wound healing developed with aminated nanofibers with and without EGF were successfully prepared. The morphology did not change during neither after the grafted process, the number of EGF attached to the fibers were 2.67 × 10


Addictive drugs are habit-forming. Addiction is a learned behavior; repeated exposure to addictive drugs can stamp in learning. Dopamine-depleted or dopamine-deleted animals have only unlearned reflexes; they lack learned seeking and learned avoidance. Burst-firing of dopamine neurons enables learning—long-term potentiation (LTP)—of search and avoidance responses. It sets the stage for learning that occurs between glutamatergic sensory inputs and GABAergic motor-related outputs of the striatum; this learning establishes the ability to search and avoid. Independent of burst-firing, the rate of single-spiking—or “pacemaker firing”—of dopaminergic neurons mediates motivational arousal. Motivational arousal increases during need states and its level determines the responsiveness of the animal to established predictive stimuli. Addictive drugs, while usually not serving as an external stimulus, have varying abilities to activate the dopamine system; the comparative abilities of different addictive drugs to facilitate LTP is something that might be studied in the future. Addictive drugs are habit-forming. Here we use the phase “habit-forming broadly  to referDopamine-deficient animals are born with minimal—learned in utero—knowledge of the environment. These animals have normal reflexes: they can swallow food if it is placed in their mouth  and theyGenetically modified neonates that cannot synthesize dopamine in the brain , like adThe dopamine system is activated by three kinds of external stimuli: rewarding stimuli, punishing stimuli, and novel stimuli. When activated by rewards or punishers, portions of the dopamine system discharge in bursts , 28–32, The primary sensory inputs to the dopamine system—driving this release—are glutamatergic and perhaps cholinergic terminals from cell bodies of the latero-dorsal and pedunculopontine tegmental nuclei , 39; simtravelling from the unconditioned rewards and punishers to their predictors; rather, the process of burst-firing develops anew in response to predictors that involve a Hebbian mechanism [The burst-firing in response to predictors of rewards or punishers develops with age, as the animal learns about the environment. The burst-responses should not really be seen as echanism , 43. Hebechanism . When buBurst-firing of the dopamine system is only a first step in the learning; the formation of the synapses for searching develops in other cellular elements. Dopamine bursting enables development of long-term potentiation (LTP) and long-term depression (LTD), and, in the striatum, this occurs between glutamatergic sensory inputs and GABAergic motor-related outputs , 46. DopWhereas burst responding of the dopamine system is elicited by external stimuli, dopaminergic single discharges also spontaneously occur; these discharges are identified as pacemaker firing because they result from a depolarizing current within the dopaminergic cells themselves . Such diMotivational arousal is a state variable; it regulates readiness to respond to external stimuli. While rewards and punishers elicit responses regardless of emotional state, it is predictors of rewards or punishers that depend on motivational arousal. In resting animals, it is pacemaker firing that varies as a function of internal state and determines when, and to what degree, the animal responds to reward-predictors. Burst-firing can also influence motivational arousal; consider the behavior of an animal when a pheromone-emitting conspecific passes nearby. Motivational arousal varies over time and, in resting animals, determines when a previously sated animal starts to become hungry and interested in seeking food.In a resting animal, the release of dopamine is detected historically by microdialysis . BaselinThe evidence implicating a causal role of dopamine in motivational function comes from experiments where the dopamine system has been experimentally manipulated . These ipredictive stimuli in the environment. The distinction here is between predictive stimuli that lead toward or away from rewards or punishers and rewarding and punishing stimuli themselves, to which dopamine-depleted animals continue to respond.The fact that dopamine-depleted animals already have responses to rewards and punishers allows a stronger definition of motivation than has been offered in the past; the level of motivation varies with responsiveness to Motivation is not a linear function of dopamine levels and may vary with noradrenergic as well as dopaminergic motivation. Motivation is low when dopamine levels are low, and it increases as dopamine levels start to increase. However, when dopamine levels are doubled or tripled—such levels as are induced by self-administered doses of amphetamine , cocainein anticipation of, or in fear of, expected aversive symptoms.Wheeler and colleagues have suggested conditions in which cocaine-predictive cues can become associated with negative affect –79. The delayed cocaine availability that became aversive. Delayed cocaine availability is not well associated with dopamine release; dopamine release is directly controlled by what happens in seconds after the prediction [In the Wheeler studies, animals were given series of 30 or 45 min-long, intra-oral taste stimuli that preceded 2 h sessions of intravenous saline or cocaine self-administration. After several days of training the facial expression elicited by the taste cues  and the ediction . The immRoles for dopamine in reward theory –82 and aAmphetamine and cocaine The role of dopamine in the rewarding effects of the psychomotor stimulants—amphetamine and cocaine—are strongly established. Self-administered doses of amphetamine [hetamine  or cocaihetamine  elevate hetamine , 95, 96.hetamine , 95, 96.hetamine  and temphetamine . These lhetamine , 98. Finhetamine –101.Opiates Heroin self-administration is also clearly dopamine-dependent. It more than triples resting dopamine levels [e levels , and whie levels , evidence levels . An impoe levels  where the levels ; the lace levels  does note levels  rule oute levels , 107.Nicotine Self-administration of nicotine also appears to be dopamine-dependent. Nicotine self-administration causes burst-firing of dopaminergic neurons [ neurons , 109 and neurons . It is d neurons  and sele neurons . Nicotin neurons –115. Nic neurons . Nicotin neurons , 118, a  neurons .Ethanol The evidence that dopamine is important for the rewarding effects of ethanol is also substantial but weaker than that supporting dopamine involvement in stimulant or opiate reward. Part of the problem is that we still have no animal model of self-administration that is sufficient to maintain intoxication [xication ; rats caxication –124, andxication , 126, hoxication , 128; etxication . Ethanolxication , and incDopamine antagonists decrease lever-pressing for ethanol in a sucrose-fading procedure , 131; thCannabis There are many cannabinoids, some of which have psychoactive effects and remain to be studied. The primary psychoactive ingredient in marijuana is ∆9-tetrahydrocannabinol (THC). While some studies have reported that this agent is self-administered intravenously by rodents [ rodents  and non- rodents  and incr rodents –139, oth rodents , 141. Ne rodents , 143. Ho rodents .THC is an unusual agent; two of its endogenous analogues—anandamide, 2-arachidonylglycerol—are expressed by dopaminergic (and other) neurons and are released when dopaminergic neurons fire; they influence dopamine turnover through actions on inputs to the dopamine system , 146. THBarbiturates and benzodiazepines Much less is known about self-administered doses of barbiturates or benzodiazepines. Barbiturates [A receptors [iturates , 149 anditurates , 151 areiturates , 153 by eceptors –157. At eceptors –161 and eceptors .Caffeine Caffeine is self-administered by animals [ animals , 163 and animals . A dopam animals . Volatiz animals . The mec animals . Other s animals  or ethan animals , 169.Learned behavior—perhaps all or almost-all learned behavior—depends on dopamine function; dopamine deficient animals fail to learn to search for food or other rewards and fail to learn to avoid predictable punishers. Dopamine neurons discharge in bursts when triggered by external stimuli, and this burst-firing enables formation of potentiated glutamate-GABA signaling that is critical for learned searching. Dopamine neurons also discharge in slower single-impulse pacemaker firing and the rate of this firing appears to determine motivation in resting (inanimate) animals. The ability of addictive drugs to cause burst-like discharges in the dopamine system is the broadly assumed correlate of addiction, but the direct evidence for this assumption is linked strongly to amphetamine, cocaine, and opiates; the evidence is weaker for nicotine and alcohol, cannabis, barbiturates, benzodiazepines, and caffeine. The abilities of different addictive drugs to enable long-term potentiation and facilitate habit formation via dopaminergic mechanisms should be compared in future studies.


In order to explore the influence of childhood family routines on adult depression and the mediating role of tolerance of uncertainty and rumination, the current study tested 818 participants by adopting four questionnaires. The results of structural equation modeling revealed that (1) family routines had a negative effect on depression among Chinese college students; (2) family routines were found to have a positive effect on tolerance of uncertainty, and tolerance of uncertainty was a bridge linking family routines and depression; (3) family routines had a significant effect on depression through rumination; (4) the relationship between family routines and depression was partially mediated by the chain of tolerance of uncertainty and rumination. The result reveals not only the fact that childhood family routines have significant influence on college students' depression but also the mechanism of childhood family routines that affect college students' depression. The limitations and implications of our study were also discussed. Depression has an adverse effect on individual's work performance, interpersonal relationships, economic status, and even suicidal inclination  refers to individual's differences in cognitive, emotional, or behavioral response propensity when responding to uncertain situations , with an effective rate of 92.01%.x2/df = 6.51(p < 0.001), CFI = 0.94, NNFI = 0.93, RMSEA = 0.09, SRMR = 0.068].The Family Routines Scale (FRS) was developed by Zhang , who adox2/df = 6.74(p < 0.001), CFI = 0.97, NNFI = 0.96, RMSEA = 0.086, SRMR = 0.043].The Intolerance of Uncertainty Scale (IUS) is a Chinese version of the IUS scale revised by Li et al.  based onx2/df = 5.11(p < 0.001), CFI = 0.96, NNFI = 0.95, RMSEA = 0.076, SRMR = 0.053].The Ruminative Response Scale (RRS) was developed by Nolen-Hoeksema  and revix2/df = 3.52(p < 0.001), CFI = 0.91, NNFI = 0.90, RMSEA = 0.059, SRMR = 0.052].The Self-rating Depression Scale (SDS) was developed by Zung  and reviCommon method bias may exist because all of the data were generated by self-report, which may decrease the validity of the results. Generally, there are two ways of controlling common method bias, procedural remedies and statistical remedies. Procedural remedies refer to control measures incorporated into the process of a study's design and measurement by researchers. In this study, we kept strict principles of confidentiality and voluntarism, and asked participants to truthfully fill out each item in the questionnaire. We used the class collective measured approach to acquire the data, and recycled the questionnaires immediately after each survey was completed. The directions of all questionnaires were unified in the same format. These can partially control the Common method bias.2= 15888.98, df = 2627, χ2/df = 6.05, RMSEA = 0.12, CFI = 0.58, NFI = 0.56, NNFI = 0.57, and SRMR = 0.11, which indicates that there was no serious common method bias problem in each variable in this study.In addition, statistical remedies involve a statistical test that is applied after data collection. A confirmatory factor analysis (CFA) was used to test the common method bias in this study, and the one factor model fitting indexes were χThe mean value, standard deviation, and correlation coefficients of each variable were statistically analyzed using SPSS 23.0. As shown in p < 0.001), and H1 is supported.LISREL 8.80 and the SPSS Macro Program PROCESS version 3.3) were used to test the structural equation model. The results are represented in .3 were uSecondly, models 2 and 3 were established with tolerance of uncertainty and rumination as single mediators. Through the model 4 of the SPSS Macro Program PROCESS, the bootstrap method was used to repeat the sampling 5,000 times to test the mediating effect. The results show that the mediating effect of tolerance of uncertainty was −0.0184, with 95% confidence interval , excluding 0, thus verifying H2. The mediating effect of rumination was −0.0249, with 95% confidence interval , excluding 0. Based on the results, H3 was verified.Finally, the chain multiple mediation effect was tested. According to the model 6 of the SPSS Macro Program PROCESS, the 95% confidence interval of the mediating effect was estimated by extracting 5,000 bootstrap samples, and the chain multiple mediation effect of tolerance of uncertainty and rumination was tested significantly. The results are shown in x2/df = 5.141(p < 0.001), CFI = 0.96, NFI = 0.96, NNFI = 0.95, RMSEA = 0.074, SRMR = 0.042], indicating that the model can be well-established. According to the above analysis, the chain mediation model can be constructed (see The results of structural equation model analysis using LISREL 8.80 show that the index of the model fits well (cted see .Conventional family studies have mostly focused on the impact on the physical and mental development of childhood (Lanza and Drabick, Why do family routines in childhood still have an impact on depression in adult college students after their childhood? On the one hand, the reason might be that the unpredictability of unstable and unstructured family routines for family activities increases the risk of depression in adulthood. There are ample studies proposing that an individual's unpredictable experience is closely related to depression-related processing such as learned helplessness, perception of stress, psychological well-being, and physiological stress response (Manczak et al., The results of this study found that family routines significantly correlated to individual tolerance of uncertainty, and affect depression through tolerance of uncertainty. It demonstrates that children would be in a chaotic, unpredictable and uncertain environment and thus result in a lack of sense of control over the environment if good and structured family routines are not established in the family. Once a child develops low tolerance of uncertainty, low tolerance of uncertainty will force him be more inclined to feel anxiety and depression when he encounters uncertain situations or events, even after his adulthood (Buhr and Dugas, The results of this study also show that family routines significantly correlated to individual rumination, and affect depression through rumination. Some researchers have pointed out that the reason for rumination is linked to early childhood experience (Nolen-Hoeksema et al., Finally, this study also found that family routines can also affect depression through the chain-mediated role of tolerance of uncertainty and rumination. This shows that individuals with low tolerance for uncertainty may think repeatedly, hoping to learn more about the situation, and thereby reducing their sense of uncertainty (Liao and Wei, The current research inspires us to pay attention to the influence of family routines on individual development, because it may last a lifetime. In order to provide a good family environment for children's development, it is of great importance to establish predictable, stable, and structured family routines, and to decrease the occurrence of depression by improving individual tolerance of uncertainty and reducing the level of rumination. This study still has the following limitations and deficiencies. First, in terms of research methods, the cross-sectional data collection makes it hard to make causal attributions and result application of the results to other populations. To address this limitation in subsequent research, prospective multi-site studies should be undertaken to allow the results to be generalized to a larger population of individuals. Second, participants provided retrospective reports of their childhood family routines. Although many studies in this area have adopted such research methods (Ballash et al., The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.YZY and JYZ conducted the statistical analyses and wrote and revised the manuscript, as well as the management of the original data. SHD conceptualized the aims and hypotheses, wrote and revised the manuscript, participated in the overall design and coordination of the original data collection, performed the original data measurements, and helped perform the statistical analysis in the current study. All authors gave critical comments, read, and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.