EMBnet.journal最新文献

EMBnet.journal

Pub Date : 2024-05-22 DOI: 10.14806/ej.29.0.1049

Eleni Papakonstantinou, Konstantina Dragoumani, G. Chrousos, Dimitrios Vlachakis

Epigenetics is the study of heritable changes in gene expression that occur without changes to the underlying DNA sequence. Epigenetic modifications can include DNA methylation, histone modifications, and non-coding RNAs, among others. These modifications can influence the expression of genes by altering the way DNA is packaged and accessed by transcriptional machinery, thereby affecting cellular function and behavior. Epigenetic modifications can be influenced by a variety of factors, including environmental exposures, lifestyle factors, and aging, whilst abnormal epigenetic modifications have been implicated in a range of diseases, including cancer, neurodegenerative disorders, and cardiovascular disease. The study of epigenetics has the potential to provide new insights into the mechanisms of disease and could lead to the development of new diagnostic and therapeutic strategies. Exosomes can transfer epigenetic information to recipient cells, thereby influencing various physiological and pathological processes, and the identification of specific epigenetic modifications that are associated with a particular disease could lead to the development of targeted therapies that restore normal gene expression patterns. In recent years, the emerging role of exosomal epigenetics in human breast milk, highlighting its significance in infant nutrition and immune development. Milk exosomes are shown to carry epigenetic regulators, including miRNAs and long non-coding RNAs, which can modulate gene expression in recipient cells. These epigenetic modifications mediated by milk exosomal RNAs have implications for the development of the gastrointestinal tract, immune system, and metabolic processes in infants.

表观遗传学是一门研究基因表达发生的可遗传变化的学科，这些变化发生时并没有改变底层 DNA 序列。表观遗传修饰包括 DNA 甲基化、组蛋白修饰和非编码 RNA 等。这些修饰可通过改变 DNA 的包装方式和转录机制的访问方式来影响基因的表达，从而影响细胞的功能和行为。表观遗传修饰会受到环境暴露、生活方式和衰老等多种因素的影响，而异常的表观遗传修饰则与癌症、神经退行性疾病和心血管疾病等一系列疾病有关。对表观遗传学的研究有可能为了解疾病的机理提供新的视角，并有可能开发出新的诊断和治疗策略。外泌体可将表观遗传信息传递给受体细胞，从而影响各种生理和病理过程，识别与特定疾病相关的特定表观遗传修饰可开发出恢复正常基因表达模式的靶向疗法。近年来，外泌体表观遗传学在人类母乳中的作用不断显现，凸显了其在婴儿营养和免疫发育中的重要意义。研究表明，母乳外泌体携带表观遗传调节因子，包括 miRNA 和长非编码 RNA，可调节受体细胞的基因表达。这些由牛奶外泌体RNA介导的表观遗传修饰对婴儿的胃肠道发育、免疫系统和新陈代谢过程都有影响。

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引用次数: 0

Milk exosomes and a new way of communication between mother and child 牛奶外泌体和母婴沟通的新方式

EMBnet.journal

Pub Date : 2024-05-22 DOI: 10.14806/ej.29.0.1050

Eleni Papakonstantinou, Konstantina Dragoumani, Thanasis Mitsis, G. Chrousos, D. Vlachakis

Extracellular vesicles (EVs) are a heterogeneous group of lipid-bound vesicles released by cells into the extracellular space. EVs are an important mediator of intercellular communications and carry a wide variety of molecules that exert a biological function, such as lipids, nucleic acids, proteins, ions, and adenosine triphosphate (ATP). Extracellular vesicles are classified into microvesicles, exosomes, and apoptotic bodies depending on their biogenesis and size. Exosomes are spherical lipid-bilayer vesicles with a diameter of about 40 to 100 nm. Exosomes originate from intracellular endosomal compartments, while microvesicles originated directly from a cell’s plasma membrane and apoptotic bodies originate from cells undergoing apoptosis and are released via outward blebbing and fragmentation of the plasma membrane. Specifically, exosomes have garnered great attention since they display great potential as both biomarkers and carriers of therapeutic molecules.

细胞外囊泡（EVs）是由细胞释放到细胞外空间的一类脂质结合囊泡。胞外囊泡是细胞间通讯的重要媒介，携带多种具有生物功能的分子，如脂类、核酸、蛋白质、离子和三磷酸腺苷（ATP）。细胞外囊泡根据其生物发生和大小可分为微囊泡、外泌体和凋亡体。外泌体是直径约为 40 至 100 纳米的球形脂质层囊泡。外泌体来源于细胞内的内泌体隔室，而微囊泡直接来源于细胞的质膜，凋亡体则来源于发生凋亡的细胞，通过质膜向外裂解和破碎释放出来。特别是外泌体，因其作为生物标记物和治疗分子载体的巨大潜力而备受关注。

引用次数: 0

Fingerprinting Breast Milk; insights into Milk Exosomics 母乳指纹识别；深入了解牛奶外泌体研究

EMBnet.journal

Pub Date : 2024-05-22 DOI: 10.14806/ej.29.0.1048

Eleni Papakonstantinou, Konstantina Dragoumani, Antonia Mataragka, F. Bacopoulou, Christos Yapijakis, Nikolaos AA Balatsos, Katerina Pissaridi, Dimitris Ladikos, Aspasia Efthymiadou, George Katsaros, E. Gikas, Pantelis Hatzis, Martina Samiotaki, M. Aivaliotis, Vasileios Megalooikonomou, Antonis Giannakakis, C. Iliopoulos, Erik Bongcam-Rudloff, Sofia Kossida, Elias Eliopoulos, G. Chrousos, Dimitrios Vlachakis

Breast milk, often referred to as "liquid gold," is a complex biofluid that provides essential nutrients, immune factors, and developmental cues for newborns. Recent advancements in the field of exosome research have shed light on the critical role of exosomes in breast milk. Exosomes are nanosized vesicles that carry bioactive molecules, including proteins, lipids, nucleic acids, and miRNAs. These tiny messengers play a vital role in intercellular communication and are now being recognized as key players in infant health and development. This paper explores the emerging field of milk exosomics, emphasizing the potential of exosome fingerprinting to uncover valuable insights into the composition and function of breast milk. By deciphering the exosomal cargo, we can gain a deeper understanding of how breast milk influences neonatal health and may even pave the way for personalized nutrition strategies.

母乳常被称为 "液体黄金"，是一种复杂的生物液体，为新生儿提供必需的营养物质、免疫因子和发育线索。外泌体研究领域的最新进展揭示了外泌体在母乳中的关键作用。外泌体是一种纳米级囊泡，携带生物活性分子，包括蛋白质、脂类、核酸和 miRNA。这些微小的信使在细胞间通信中发挥着重要作用，目前已被认为是婴儿健康和发育的关键因素。本文探讨了新兴的乳汁外泌体研究领域，强调了外泌体指纹图谱在揭示母乳成分和功能方面的潜在价值。通过破译外泌体货物，我们可以更深入地了解母乳如何影响新生儿健康，甚至为个性化营养策略铺平道路。

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引用次数: 0

Ds-Seq: An Integrated Pipeline for In Silico Small RNA Se-quence Analysis for Host-pathogen Interaction Studies Ds-Seq：用于宿主-病原体相互作用研究的硅学小 RNA 序列分析集成管道

EMBnet.journal

Pub Date : 2024-01-25 DOI: 10.14806/ej.29.0.1037

Temitayo A. Olagunju, Angela Uche Makolo, Andreas Gisel

Plant-pathogen interactions activate molecular activities wherein the host defends the pathogen while the pathogen tries to suppress the plant response. Small RNAs (sRNAs) mediate major mechanisms, including post-transcriptional gene silencing, histone modification and DNA methylation by which plants respond to the presence of pathogens. Genome-wide profiling of host and pathogen sRNAs is therefore pivotal to uncovering the mechanisms underlying the host-pathogen interaction and mechanisms for host resistance. sRNA high throughput sequencing (HTS) data analysis often involves multiple stages/tools. Most necessary tools are accessible only through the command line, making it challenging for those without a high level of Unix/Linux skills. Furthermore, installation of some of these tools may become difficult due to dependencies and software version compatibility. We have developed an integrated open-source pipeline, Ds-Seq, for end-to-end in silico analysis of sRNA HTS data with improved reproducibility. The pipeline combines in-house scripts and public tools in a shell script, which can be invoked with a single command. The pipeline's usefulness has been demonstrated with testing on publicly available and published data from independent sRNA-seq datasets of host-pathogen interaction studies. Ds-Seq is available on GitHub, while a Docker image can be obtained from the Docker hub.Availability: Ds-Seq is freely available from the GitHub repository at https://github.com/CEPHAS-01/small-RNASeq.ngs and Docker hub with ID cephas/ds-seq (https://hub.docker.com/r/cephas/ds-seq).

植物与病原体的相互作用激活了分子活动，宿主在其中防御病原体，而病原体则试图抑制植物的反应。小 RNA（sRNA）介导了主要的机制，包括转录后基因沉默、组蛋白修饰和 DNA 甲基化，植物通过这些机制对病原体的存在做出反应。因此，对宿主和病原体 sRNA 进行全基因组分析对于揭示宿主与病原体之间的相互作用机制和宿主抗性机制至关重要。sRNA 高通量测序（HTS）数据分析通常涉及多个阶段/工具。大多数必要的工具只能通过命令行访问，这对没有高水平 Unix/Linux 技能的人来说具有挑战性。此外，由于依赖性和软件版本兼容性问题，安装其中一些工具可能会变得很困难。我们开发了一个集成的开源管道 Ds-Seq，用于对 sRNA HTS 数据进行端到端的硅学分析，提高了可重复性。该管道将内部脚本和公共工具整合到一个 shell 脚本中，只需一个命令即可调用。通过对宿主与病原体相互作用研究中独立 sRNA-seq 数据集的公开数据和已发表数据的测试，证明了该管道的实用性。Ds-Seq 可在 GitHub 上获取，Docker 镜像可从 Docker hub 获取：Ds-Seq 可从 GitHub 存储库 https://github.com/CEPHAS-01/small-RNASeq.ngs 和 Docker hub 免费获取，ID 为 cephas/ds-seq (https://hub.docker.com/r/cephas/ds-seq)。

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引用次数: 0

The Intersection of Artificial Intelligence and Precision Endocrinology. 人工智能与精准内分泌学的交汇点。

EMBnet.journal

Pub Date : 2024-01-01 Epub Date: 2024-09-09 DOI: 10.14806/ej.30.0.1052

Dimitrios Vlachakis, Konstantina Dragoumani, Eleni Papakonstantinou, George P Chrousos

Bioinformatics and artificial intelligence (AI) have emerged as transformative tools in modern medicine, revolutionising the landscape of medical diagnosis and treatment. Herein, we provide an overview of the synergistic relationship between bioinformatics and AI, elucidating their pivotal roles in deciphering complex biological data and advancing precision medicine and, in particular, endocrinology. We explore various applications of bioinformatics and AI in medical research, including genomic analysis, drug discovery, disease diagnosis, and personalised treatment strategies. Additionally, we discuss challenges and future directions in leveraging these technologies to enhance healthcare outcomes.

生物信息学和人工智能（AI）已成为现代医学的变革性工具，彻底改变了医疗诊断和治疗的面貌。在本文中，我们将概述生物信息学和人工智能之间的协同关系，阐明它们在破译复杂生物数据、推进精准医学，特别是内分泌学方面的关键作用。我们探讨了生物信息学和人工智能在医学研究中的各种应用，包括基因组分析、药物发现、疾病诊断和个性化治疗策略。此外，我们还讨论了利用这些技术提高医疗成果所面临的挑战和未来发展方向。

引用次数: 0

The effect of the planned behaviour theory and the transtheoretical behaviour model on physical activity. A systematic review. 计划行为理论与跨理论行为模型对身体活动的影响。系统回顾。

EMBnet.journal

Pub Date : 2023-09-22 DOI: 10.14806/ej.29.0.1046

Anastasia Dermatis, Flora Bacopoulou, Ioulia Kokka, Dimitrios Vlachakis, Georgios Lyrakos, Despina Menti, Christina Darviri

Systematic physical activity (PA) is crucial in preventing illnesses that can become life-threatening, such as colon and breast cancer, heart disease and ischemic stroke, cardio-respiratory disease, type II diabetes, and depression. Many theory–based interventions have been applied to achieve positive outcomes in an individual's behavioural change and the ability to engage in systematic PA. This systematic review investigates the influence of the Transtheoretical model of behaviour (TTM) and the theory of planned behaviour (TPB) on PA. A substantial search in Science Direct, Wiley Online Library databases and PubMed was performed to obtain articles about the topic. Data exportation was possible after the reviewers applied exclusion–inclusion criteria to estimate evidence quality. Empirical evidence was assessed with the CONSORT checklist to appraise the risk of bias. The primary search identified 195 studies. Of those, ten original studies were comprised. All studies indicated a positive influence of TPB and TTM on physical activity in non–health and healthy populations. In particular, it was found to have an impact on energy expenditure, balance and body strength. Theory-based interventions are notably effective in promoting physical activity behaviour. Researchers and health professionals must select and utilise interventions based on the above mentioned theories and aim to enhance PA behavioural change on individual and interpersonal factors. Although the positive outcomes of theory-based interventions on PA behaviour, it is necessary for further research to be conducted.

系统的身体活动(PA)对于预防可能危及生命的疾病至关重要，如结肠癌和乳腺癌、心脏病和缺血性中风、心肺疾病、二型糖尿病和抑郁症。许多基于理论的干预措施已被应用于在个人行为改变和参与系统PA的能力方面取得积极成果。本文系统地探讨了跨理论行为模型(TTM)和计划行为理论(TPB)对行为动机的影响。在Science Direct, Wiley Online Library数据库和PubMed中进行了大量搜索，以获得有关该主题的文章。在审稿人应用排除-纳入标准评估证据质量后，数据导出成为可能。使用CONSORT检查表对经验证据进行评估，以评估偏倚风险。初步研究确定了195项研究。其中包括10项原始研究。所有研究都表明，TPB和TTM对非健康人群和健康人群的身体活动有积极影响。特别是，它被发现对能量消耗、平衡和身体力量有影响。基于理论的干预措施在促进身体活动行为方面非常有效。研究人员和卫生专业人员必须根据上述理论选择和利用干预措施，旨在加强个人和人际因素对私人助理行为的改变。虽然基于理论的干预对私人助理行为有积极的影响，但仍有必要进行进一步的研究。

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引用次数: 0

EpiCass and CassavaNet4Dev Advanced Bioinformatics Workshop EpiCass和CassavaNet4Dev高级生物信息学研讨会

EMBnet.journal

Pub Date : 2023-06-08 DOI: 10.14806/ej.29.0.1045

A. Gisel, L. Stavolone, Temitayo A. Olagunju, Michael Landi, Renaud Van Damme, A. Niazi, L. Falquet, T. Shah, E. Bongcam-Rudloff

EpiCass and CassavaNet4Dev are collaborative projects funded by the Swedish Research Council between the Swedish University of Agriculture (SLU) and the International Institute of Tropical Agriculture (IITA). The projects aim to investigate the influence of epigenetic changes on agricultural traits such as yield and virus resistance while also providing African students and researchers with advanced bioinformatics training and opportunities to participate in big data analysis events. The first advanced bioinformatics training workshop took place from May 16th to May 18th, 2022, followed by an online mini-symposium titled "Epigenetics and crop improvement" on May 19th. The symposium featured international speakers covering a wide range of topics related to plant epigenetics, cassava viral diseases, and cassava breeding strategies. A new online and on-site teaching concept was developed for the three-day workshop to ensure maximum student participation across Western, Eastern, and Southern Africa. Initially planned in Nigeria, Kenya, Ethiopia, Tanzania, and Zambia, the workshop ultimately focused on Nigeria, Kenya, and Ethiopia due to a lack of qualified candidates in the other countries. Each classroom hosted 20 to 25 students, with at least one bioinformatician present for support. The classrooms were connected via video conferencing, whereas teachers located in different places in Africa and Europe joined the video stream to conduct teaching sessions. The workshop was divided into theoretical classes and hands-on sessions, where participants could run data analysis with support from online teachers and local bioinformaticians. To enable participants to run guided, CPU and RAM-intensive data analysis workflows and overcome local computing and internet access restrictions, a system of virtual machines (VMs) hosted in the cloud was developed. The teaching platform provided teaching and exercise materials to support the use of the VMs. Although some students could not run heavy data analysis workflows due to unforeseen restrictions in the cloud, these issues were solved. All participants had the opportunity to run the analysis steps independently in the cloud using the protocols hosted on the teaching platform.

EpiCass和CassavaNet4Dev是瑞典研究理事会在瑞典农业大学(SLU)和国际热带农业研究所(IITA)之间资助的合作项目。这些项目旨在调查表观遗传变化对产量和病毒抗性等农业性状的影响，同时为非洲学生和研究人员提供先进的生物信息学培训和参与大数据分析活动的机会。第一次高级生物信息学培训研讨会于2022年5月16日至5月18日举行，随后于5月19日举行了题为“表观遗传学与作物改良”的在线小型研讨会。研讨会邀请了来自世界各地的发言者，讨论了与植物表观遗传学、木薯病毒病和木薯育种策略有关的广泛主题。为为期三天的研讨会制定了新的在线和现场教学概念，以确保西部、东部和南部非洲的学生最大限度地参与其中。讲习班最初计划在尼日利亚、肯尼亚、埃塞俄比亚、坦桑尼亚和赞比亚举办，但由于其他国家缺乏合格的候选人，讲习班最终将重点放在尼日利亚、肯尼亚和埃塞俄比亚。每个教室容纳20至25名学生，至少有一名生物信息学家在场提供支持。教室通过视频会议连接，而位于非洲和欧洲不同地方的教师加入视频流进行教学。研讨会分为理论课和实践课，参与者可以在在线教师和当地生物信息学家的支持下进行数据分析。为了使参与者能够运行有指导的、CPU和ram密集型的数据分析工作流程，并克服本地计算和互联网访问限制，开发了一个托管在云中的虚拟机系统。教学平台提供教学和练习材料，支持虚拟机的使用。尽管由于云中的不可预见的限制，一些学生无法运行繁重的数据分析工作流程，但这些问题都得到了解决。所有参与者都有机会使用教学平台上托管的协议在云中独立运行分析步骤。

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引用次数: 0

On potential limitations of differential expression analysis with non-linear machine learning models 非线性机器学习模型差分表达式分析的潜在局限性

EMBnet.journal

Pub Date : 2023-03-08 DOI: 10.14806/ej.28.0.1035

G. Sabbatini, L. Manganaro

Recently, there has been a growing interest in bioinformatics toward the adoption of increasingly complex machine learning models for the analysis of next-generation sequencing data with the goal of disease subtyping (i.e., patient stratification based on molecular features) or risk-based classification for specific endpoints, such as survival. With gene-expression data, a common approach consists in characterising the emerging groups by exploiting a differential expression analysis, which selects relevant gene sets coupled with pathway enrichment analysis, providing an insight into the underlying biological processes. However, when non-linear machine learning models are involved, differential expression analysis could be limiting since patient groupings identified by the model could be based on a set of genes that are hidden to differential expression due to its linear nature, affecting subsequent biological characterisation and validation. The aim of this study is to provide a proof-of-concept example demonstrating such a limitation. Moreover, we suggest that this issue could be overcome by the adoption of the innovative paradigm of eXplainable Artificial Intelligence, which consists in building an additional explainer to get a trustworthy interpretation of the model outputs and building a reliable set of genes characterising each group, preserving also non-linear relations, to be used for downstream analysis and validation.

最近，人们对生物信息学越来越感兴趣，采用越来越复杂的机器学习模型来分析下一代测序数据，目标是疾病亚型(即，基于分子特征的患者分层)或基于风险的特定终点分类，如生存。对于基因表达数据，一种常见的方法是通过利用差异表达分析来表征新兴群体，该分析选择相关基因集，结合途径富集分析，提供对潜在生物学过程的洞察。然而，当涉及非线性机器学习模型时，差异表达分析可能会受到限制，因为模型识别的患者分组可能基于一组由于其线性性质而隐藏于差异表达的基因，从而影响随后的生物学表征和验证。本研究的目的是提供一个概念验证的例子来证明这种限制。此外，我们建议可以通过采用可解释人工智能的创新范式来克服这个问题，该范式包括建立一个额外的解释器，以获得对模型输出的可信解释，并建立一组可靠的基因来表征每个组，同时保留非线性关系，用于下游分析和验证。

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引用次数: 1

qualign: solving sequence alignment based on quadratic unconstrained binary optimisation 定性:基于二次型无约束二元优化的序列对齐求解

EMBnet.journal

Pub Date : 2023-03-08 DOI: 10.14806/ej.28.0.1020

Yuki Matsumoto, Shota Nakamura

Bioinformatics has, among others, the issue of solving complex computational problems with vast amounts of sequencing data. Recently, a new computing architecture, the annealing machine, has emerged that applies to actual problems and is available for practical use. This novel architecture can solve discrete optimisation problems by replacing algorithms designed under the von Neumann architecture. To perform computations on the annealing machine, quadratic unconstrained binary optimisation (QUBO) formulations should be constructed and optimised according to the application. In this study, we developed an algorithm under the annealing machine architecture to solve sequence alignment problems, a known fundamental process widely used in genetic analysis, such as mutation detection and genome assembly. We constructed a QUBO formulation based on dynamic programming to solve a pairwise sequence alignment and derived its general form. We compared with conventional methods to solve 40 bp of pairwise alignment problem. Our implementation, named qualign, solved sequence alignment problems with accuracy comparable to that of conventional methods. Although a small pairwise alignment was solved owing to the limited memory size of this method, this is the first step of the application of annealing machines. We showed that our QUBO formulation solved the sequencing alignment problem. In the future, increasing the memory size of annealing machine will allow annealing machines to impact a wide range of bioinformatics applications positively.Availability: the source code of qualign is available at https://github.com/ymatsumoto/qualign

除其他外，生物信息学的问题是用大量的测序数据解决复杂的计算问题。最近，出现了一种新的计算体系结构，即退火炉，它适用于实际问题，并可用于实际应用。这种新颖的架构可以通过取代在冯·诺伊曼架构下设计的算法来解决离散优化问题。为了在退火机上进行计算，需要根据应用构建二次无约束二进制优化(QUBO)公式并进行优化。在本研究中，我们开发了一种基于退机器机架构的算法来解决序列比对问题，这是一个已知的广泛应用于基因分析的基本过程，如突变检测和基因组组装。构造了一个基于动态规划的求解成对序列比对问题的QUBO公式，并推导了其一般形式。通过与传统方法的比较，解决了40 bp的成对对齐问题。我们的实现，命名为qualign，解决了序列比对问题，其精度与传统方法相当。虽然由于该方法的内存大小有限，解决了一个小的成对对齐问题，但这是退火机应用的第一步。结果表明，我们的QUBO公式解决了测序比对问题。在未来，增加退机器机的内存大小将使退机器机对广泛的生物信息学应用产生积极的影响。可用性:qualign的源代码可在https://github.com/ymatsumoto/qualign获得

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引用次数: 0

Reliability and validity of the Dyadic Coping Inventory for Financial Stress in Greek couples. 希腊夫妇财务压力二元应对量表的信度与效度。

EMBnet.journal

Pub Date : 2023-01-01 DOI: 10.14806/ej.28.0.1018

Joanne Maria Velegraki, Flora Bacopoulou, George P Chrousos, Marilena Panagiotou, Orsalia Gerakini, Maria Charalampopoulou, Dimitrios Vlachakis, Christina Darviri

Financial stress can negatively affect a couple's relationship. The Dyadic Coping Inventory for Financial Stress (DCIFS) instrument assesses the way couples cope with financial stress. This study sought to validate the Dyadic Coping Inventory for Financial Stress (DCIFS) in Greek. The sample included 152 Greek couples (mean age: 42.82 ± 11.94). Confirmatory factor analyses provided support for delegated dyadic coping and evaluation of dyadic coping. Confirmatory Factor Analysis results supported a 33-item version consisting of the following subscales for both men and women: Stress Communication by Oneself and by Partner, Emotion and Problem-Focused Supportive Dyadic Coping (DC) by Oneself and by Partner, Negative DC by Oneself and by Partner, Emotion and Problem-Focused Common DC, and Evaluation of DC. The Dyadic Coping Inventory questionnaire and Perceived Stress Scale were used to assess the criterion validity of DCIFS.

经济压力会对夫妻关系产生负面影响。财务压力双元应对量表(DCIFS)工具评估夫妻应对财务压力的方式。本研究旨在验证希腊文金融压力二元应对量表(DCIFS)。样本包括152对希腊夫妇(平均年龄:42.82±11.94)。验证性因子分析为授权的二元应对和二元应对的评价提供了支持。验证性因子分析结果支持由以下33个分量表组成的版本，包括男性和女性:自己和伴侣的压力沟通，自己和伴侣的情绪和问题关注的支持性二元应对(DC)，自己和伴侣的消极DC，情绪和问题关注的共同DC和DC评价。采用二元应对量表和感知压力量表对DCIFS量表的效度进行评估。

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引用次数: 0