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@article{Saubin2022,

title = {Improving sustainable crop protection using population genetics concepts},

author = {Méline Saubin and Clémentine Louet and Lydia Bousset and Frédéric Fabre and Pascal Frey and Isabelle Fudal and Frédéric Grognard and Frédéric Hamelin and Ludovic Mailleret and Solenn Stoeckel and Suzanne Touzeau and Benjamin Petre and Fabien Halkett},

url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/mec.16634},

doi = {/10.1111/mec.16634},

year  = {2022},

date = {2022-07-30},

urldate = {2022-07-30},

journal = {Molecular Ecology},

number = {0},

pages = {1-11},

abstract = {Growing genetically resistant plants allows pathogen populations to be controlled and reduces the use of pesticides. However, pathogens can quickly overcome such resistance. In this context, how can we achieve sustainable crop protection? This crucial question has remained largely unanswered despite decades of intense debate and research effort. In this study, we used a bibliographic analysis to show that the research field of resistance durability has evolved into three subfields: (1) “plant breeding” (generating new genetic material), (2) “molecular interactions” (exploring the molecular dialogue governing plant–pathogen interactions) and (3) “epidemiology and evolution” (explaining and forecasting of pathogen population dynamics resulting from selection pressure[s] exerted by resistant plants). We argue that this triple split of the field impedes integrated research progress and ultimately compromises the sustainable management of genetic resistance. After identifying a gap among the three subfields, we argue that the theoretical framework of population genetics could bridge this gap. Indeed, population genetics formally explains the evolution of all heritable traits, and allows genetic changes to be tracked along with variation in population dynamics. This provides an integrated view of pathogen adaptation, in particular via evolutionary–epidemiological feedbacks. In this Opinion Note, we detail examples illustrating how such a framework can better inform best practices for developing and managing genetically resistant cultivars.},

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pubstate = {published},

tppubtype = {article}

}

@article{Zhao2021,

title = {Is coronavirus-related research becoming more interdisciplinary? A perspective of co-occurrence analysis and diversity measure of scientific articles},

author = {Yi Zhao and Lifan Liu and Chengzhi Zhang},

doi = {https://doi.org/10.1016/j.techfore.2021.121344},

year  = {2021},

date = {2021-11-08},

urldate = {2021-11-08},

journal = {Technological Forecasting and Social Change},

volume = {121344},

abstract = {The outbreak of coronavirus disease 2019 (COVID-19) has had a significant repercussion on the health, economy, politics and environment, making coronavirus-related issues more complicated and difficult to adequately address by relying on a single field. Interdisciplinary research can provide an effective solution to complex issues in the related field of coronavirus. However, whether coronavirus-related research becomes more interdisciplinary still needs corroboration. In this study, we investigate interdisciplinary status of the coronavirus-related fields via the COVID-19 Open Research Dataset (CORD-19). To this end, we calculate bibliometric indicators of interdisciplinarity and apply a co-occurrence analysis method. The results show that co-occurrence relationships between cited disciplines have evolved dynamically over time. The two types of co-occurrence relationships, Immunology and Microbiology & Medicine and Chemical Engineering & Chemistry, last for a long time in this field during 1990–2020. Moreover, the number of disciplines cited by coronavirus-related research increases, whereas the distribution of disciplines is uneven, and this field tends to focus on several dominant disciplines such as Medicine, Immunology and Microbiology, Biochemistry, Genetics and Molecular Biology. We also measure the disciplinary diversity of COVID-19 related papers published from January to December 2020; the disciplinary variety shows an upward trend, while the degree of disciplinary balance shows a downward trend. Meanwhile, the comprehensive index 2Ds demonstrates that the degree of interdisciplinarity in coronavirus field decreases between 1990 and 2019, but it increases in 2020. The results help to map the interdisciplinarity of coronavirus-related research, gaining insight into the degree and history of interdisciplinary cooperation.},

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pubstate = {published},

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}

@article{Xu2021,

title = {Exploring the Interdisciplinary Nature of Precision Medicine：Network Analysis and Visualization},

author = {Xin Xu and Jiming Hu and Xiaoguang Lyu and Huang He and Cheng Xingyu },

doi = {10.2196/23562 },

year  = {2021},

date = {2021-01-11},

urldate = {2021-01-11},

journal = {JMIR Medical Informatics},

abstract = {The aim of this study is to present the nature of interdisciplinary collaboration in precision medicine based on co-occurrences and social network analysis. A total of 7544 studies about precision medicine, published between 2010 and 2019, were collected from the Web of Science database. We analyzed interdisciplinarity with descriptive statistics, co-occurrence analysis, and social network analysis. An evolutionary graph and strategic diagram were created to clarify the development of streams and trends in disciplinary communities. The results indicate that 105 disciplines are involved in precision medicine research and cover a wide range. However, the disciplinary distribution is unbalanced. Current cross-disciplinary collaboration in precision medicine mainly focuses on clinical application and technology-associated disciplines. The characteristics of the disciplinary collaboration network are as follows: (1) disciplinary cooperation in precision medicine is not mature or centralized; (2) the leading disciplines are absent; (3) the pattern of disciplinary cooperation is mostly indirect rather than direct. There are 7 interdisciplinary communities in the precision medicine collaboration network; however, their positions in the network differ. Community 4, with disciplines such as genetics and heredity in the core position, is the most central and cooperative discipline in the interdisciplinary network. This indicates that Community 4 represents a relatively mature direction in interdisciplinary cooperation in precision medicine. Finally, according to the evolution graph, we clearly present the development streams of disciplinary collaborations in precision medicine. We describe the scale and the time frame for development trends and distributions in detail. Importantly, we use evolution graphs to accurately estimate the developmental trend of precision medicine, such as biological big data processing, molecular imaging, and widespread clinical applications.},

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pubstate = {published},

tppubtype = {article}

}

@article{Gaulda2020,

title = {Analyse en réseau par fouille de données textuelles systématique du concept de psychiatrie personnalisée et de précision},

author = {Christophe Gauld and Jean-Arthur M. Franchi},

url = {http://www.sciencedirect.com/science/article/pii/S0013700620302360},

doi = { https://doi.org/10.1016/j.encep.2020.08.008},

issn = {0013-7006},

year  = {2020},

date = {2020-11-12},

urldate = {2020-11-12},

journal = {L'Encéphale},

abstract = {Objectifs. – La médecine personnalisée et de précision nécessite une clarification des concepts qui y sont rattachés. À notre connaissance, il n’existe pas d’exploration systématique de la littérature portant sur les dimensions et les concepts de la psychiatrie personnalisée et de précision et sur leurs usages dans les domaines neuroscientifiques et génétiques. Cet article propose donc d’explorer les dimensions et les concepts de la psychiatrie personnalisée et de précision.

Méthodes. – Une analyse en réseau par fouille de données textuelles systématique issue d’une revue exhaustive de la littérature internationale autour des termes de “precision psychiatry” et de “personalized psychiatry” a été réalisée. Cette fouille de données textuelles a été représentée sous forme d’un réseau permettant d’analyser les dimensions et les concepts de la psychiatrie personnalisée et de précision. Résultats. – La psychiatrie personnalisée et de précision renvoie à six dimensions retrouvées au sein de l’analyse du réseau textuel. Ces six dimensions correspondent aux domaines scientifiques qui étu- dient la psychiatrie personnalisée et de précision, à savoir : la génétique, la pharmacogénétique, les approches computationnelles, le raffinement des essais thérapeutiques, les biomarqueurs et la stadifica- tion. L’analyse des termes renvoie à un ensemble de concepts hétérogènes.

Conclusions. – L’hétérogénéité retrouvée dans la littérature sur la psychiatrie personnalisée et de précision peut témoigner d’un manque d’un cadre théorique pluraliste et intégratif. Ce cadre de travail pourrait être basé sur un formalisme naturalisant mais non réducteur, conscient des enjeux sociétaux des sciences et de leur implémentation dans les dispositifs de recherche et cliniques de la psychiatrie.

Objectives

The current challenges of psychiatric nosology and semiology are part of an interdisciplinary and integrative framework. The paradigm of the personalized and precision psychiatry proposes to study this discipline according to new approaches and methodologies. Personalized and precision psychiatry therefore requires clarification of its concepts. To our knowledge, there is no systematic exploration of the literature on the application of the concepts of personalized and precision medicine in the field of psychiatry. This article proposes thus to explore the framework of personalized and precision medicine applied to psychiatry.

Methods

We explored the framework of personalized and precision medicine applied to psychiatry by a textual network analysis. Firstly, we performed a systematic text-mining (Natural Language Processing) from an exhaustive review of the international literature with the terms “precision psychiatry” and “personalized psychiatry”. Secondly, this analysis of textual data allowed us to build a textual network which made it possible to visualize the most proximal terms (the most frequently associated in the literature). Finally, we extracted from the network the main dimensions explored in the scientific literature, and we studied the relative importance of each term by analyzing the network centrality. In addition, a brief bibliometric analysis was conducted.

Results

We show that personalized and precision psychiatry refers to six dimensions found in the textual network analysis which correspond to the scientific fields which study personalized and precision psychiatry: genetics, pharmacogenetics, artificial intelligence, therapeutic trials, biomarkers and staging. We explore how each dimension relates to the mechanization of psychiatric disorders. However, precision and personalized psychiatry, which tries to refine the levels of mechanistic explanations for psychiatry, suffers from a conceptual heterogeneity. Indeed, textual analysis also allows us to find terms referring to a set of heterogeneous concepts. Many methodological fields and epistemological concepts are invoked in this literature, without standardization.

Conclusions

The paradox of personalized and precision psychiatry is to associate a strong conceptual heterogeneity with a well-defined mechanistic component. Heterogeneity found in literature on personalized and precision psychiatry testifies to the lack of a pluralist and integrative theoretical framework. This framework could be based on a naturalizing but non-reducing formalism, aware of the societal challenges of the sciences and their implementation in the research and clinical systems of psychiatry.},

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tppubtype = {article}

}

@article{Lyu2020,

title = {Intellectual Structure and Evolutionary Trends of Precision Medicine Research: Coword Analysis},

author = {Xiaoguang Lyu and Jiming Hu and Weiguo Dong and Xin Xu},

url = {https://medinform.jmir.org/2020/2/e11287},

doi = {10.2196/11287},

issn = {2291-9694},

year  = {2020},

date = {2020-02-04},

urldate = {2020-02-04},

journal = {JMIR Med Inform},

volume = {8},

number = {2},

pages = {e11287},

abstract = {Background: Precision medicine (PM) is playing a more and more important role in clinical practice. In recent years, the scale of PM research has been growing rapidly. Many reviews have been published to facilitate a better understanding of the status of PM research. However, there is still a lack of research on the intellectual structure in terms of topics. Objective: This study aimed to identify the intellectual structure and evolutionary trends of PM research through the application of various social network analysis and visualization methods. Methods: The bibliographies of papers published between 2009 and 2018 were extracted from the Web of Science database. Based on the statistics of keywords in the papers, a coword network was generated and used to calculate network indicators of both the entire network and local networks. Communities were then detected to identify subdirections of PM research. Topological maps of networks, including networks between communities and within each community, were drawn to reveal the correlation structure. An evolutionary graph and a strategic graph were finally produced to reveal research venation and trends in discipline communities. Results: The results showed that PM research involves extensive themes and, overall, is not balanced. A minority of themes with a high frequency and network indicators, such as Biomarkers, Genomics, Cancer, Therapy, Genetics, Drug, Target Therapy, Pharmacogenomics, Pharmacogenetics, and Molecular, can be considered the core areas of PM research. However, there were five balanced theme directions with distinguished status and tendencies: Cancer, Biomarkers, Genomics, Drug, and Therapy. These were shown to be the main branches that were both focused and well developed. Therapy, though, was shown to be isolated and undeveloped. Conclusions: The hotspots, structures, evolutions, and development trends of PM research in the past ten years were revealed using social network analysis and visualization. In general, PM research is unbalanced, but its subdirections are balanced. The clear evolutionary and developmental trend indicates that PM research has matured in recent years. The implications of this study involving PM research will provide reasonable and effective support for researchers, funders, policymakers, and clinicians.},

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pubstate = {published},

tppubtype = {article}

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@article{Louvel2020,

title = {What’s in a name? The three genealogies of the social insocial epigenetics},

author = {Séverine Louvel},

editor = {SAGE Publications},

doi = {https://doi.org/10.1177/0539018419897001},

year  = {2020},

date = {2020-01-22},

urldate = {2020-01-22},

journal = {Social Science Information},

abstract = {Social  epigenetics  – the  study  of  the  epigenetic  mechanisms  through  which  social  environments  become biologically embodied –   epitomizes recent claims that the boundaries between the natural and the social sciences should be reduced. Relying on a bibliometric study and on a qualitative analysis of publications  in  social  epigenetics,  this   paper   investigates   how   this  research  area defines   and operationalizes  the social dimensions that may have an impact on health status and disease risk. The paper  also  addresses  how  the  social  sciences  engage  with  social  epigenetics.  First,  the  paper  traces  social epigenetics back to five epistemic backgrounds –   two in animal research (on social defeat and early-life  adversity)  and  three  in  human  studies  (on  trauma,  early-life  nutrition  and  social  adversity  over the life-course). Second, it outlines the quest for epigenetic markers of social environments, and the associated expectations and controversies. Third, it analyses the three modes of engagement of the social  sciences  with  human  studies  in  social  epigenetics:  rejection  (social  epigenetics  trapped  in  the  quest  for  a  ‘social  brain’);  warning  and  call  for  responsibility  (social  epigenetics  has  shifted  from socioeconomic   contexts   to   individual   behaviors);   and   support   and   active   contribution   (social   epigenetics may strengthen  social  studies  of  health).  This  paper  argues  that  recent  developments  in  social  epigenetics  could  strengthen  this  third  mode  of  engagement  and  expand  the  scope  of  interdisciplinary collaboration between the natural and the social sciences.},

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}