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| 1 | Placental Transfer of Anti–Tumor Necrosis Factor Agents in Pregnant Patients With Inflammatory Bowel Disease显示文摘 | Uma Mahadevan Douglas C. Wolf Marla Dubinsky Antoine Cortot Scott D. Lee Corey A. Siegel Thomas Ullman Sarah Glover John F. Valentine David T. Rubin Jocelyn Miller Maria T. Abreu | 2013 | Clinical Gastroenterology and Hepatology2013，，： | 4 |
| 2 | Loss of p53 in Enterocytes Generates an Inflammatory Microenvironment Enabling Invasion and Lymph Node Metastasis of Carcinogen-Induced Colorectal Tumors显示文摘 | Sarah Schwitalla Paul K. Ziegler David Horst Valentin Becker Irina Kerle Yvonne Begus-Nahrmann André Lechel K. Lenhard Rudolph Rupert Langer Julia Slotta-Huspenina Franz G. Bader Olivia Prazeres da Costa Markus F. Neurath Alexander Meining Thomas Kirchner | 2013 | Cancer Cell2013，，： | 2 |
| 3 | A comparison of psychiatric consultation between geriatric and non-geriatric medical inpatients 显示文摘 | Sarah E John W Valentine R | 2009 | Int J Geriatr Psychiatry2009，24，： | 1 |
| 4 | Geographies of alcohol, drinking and drunkenness: a review of progress显示文摘 | Jayne Mark Valentine Gill Holloway Sarah L | 2008 | Progress in Human Geography2008，，2： | 1 |
| 5 | Defining a Reference Set to Support Methodological Research in Drug Safety显示文摘 | Ryan Patrick B Schuemie Martijn J Welebob Emily Duke Jon Valentine Sarah Hartzema Abraham G | 2013 | Drug Safety2013，，1： | 1 |
| 6 | Loss of p53 in Enterocytes Generates an Inflammatory Microenvironment Enabling Invasion and Lymph Node Metastasis of Carcinogen-Induced Colorectal Tumors显示文摘 | Sarah Schwitalla Paul K. Ziegler David Horst Valentin Becker Irina Kerle Yvonne Begus-Nahrmann André Lechel K. Lenhard Rudolph Rupert Langer Julia Slotta-Huspenina Franz G. Bader Olivia Prazeres da Costa Markus F. Neurath Alexander Meining Thomas Kirchner | 2013 | Cancer Cell2013，，： | 1 |
| 7 | Fusion of spatiotemporal and thematic features of textual data for animal disease surveillance显示文摘Several internet-based surveillance systems have been created to monitor the web for animal health surveillance.These systems collect a large amount of news dealing with outbreaks related to animal diseases.Automatically identifying news articles that describe the same outbreak event is a key step to quickly detect relevant epidemiological information while alleviating manual curation of news content.This paper addresses the task of retrieving news articles that are related in epidemiological terms.We tackle this issue using text mining and feature fusion methods.The main objective of this paper is to identify a textual representation in which two articles that share the same epidemiological content are close.We compared two types of representations(i.e.,features)to represent the documents:(i)morphosyntactic features(i.e.,selection and transformation of all terms from the news,based on classical textual processing steps)and(ii)lexicosemantic features(i.e.,selection,transformation and fusion of epidemiological terms including diseases,hosts,locations and dates).We compared two types of term weighing(i.e.,Boolean and TF-IDF)for both representations.To combine and transform lexicosemantic features,we compared two data fusion techniques(i.e.,early fusion and late fusion)and the effect of features generalisation,while evaluating the relative importance of each type of feature.We conducted our analysis using a corpus composed of a subset of news articles in English related to animal disease outbreaks.Our results showed that the combination of relevant lexicosemantic(epidemiological)features using fusion methods improves classical morphosyntactic representation in the context of disease-related news retrieval.The lexicosemantic representation based on TF-IDF and feature generalisation(F-measure=0.92,r-precision=0.58)outperformed the morphosyntactic representation(F-measure=0.89,r-precision=0.45),while reducing the features space.Converting the features into lower granular features(i.e.,generalisation)contributed to improving the results of the lexicosemantic representation.Our results showed no difference between the early and late fusion approaches.Temporal features performed poorly on their own.Conversely,spatial features were the most discriminative features,highlighting the need for robust methods for spatial entity extraction,disambiguation and representation in internet-based surveillance systems. | Sarah Valentin Renaud Lancelot Mathieu Roche | 2023 | Information Processing in Agriculture2023，10，3： | 0 |
| 8 | 有效性的崛起和Uber的黎明(二)显示文摘2012年--Uber和独角兽的崛起(和衰落)2012年,在伦敦奥运会开幕前一个月,Uber进军伦敦,不仅改变了我们的出行方式,也开启了零工经济(Gig Economy)时代。凭借灵活的司机队伍和便捷的App功能,Uber在传统黑色出租车的海洋中迅速崛起,成为新一代颠覆者的典范。 | Sarah Vizard Charlotte Rogers Molly Fleming Matthew Valentine Matt Barker 骆佳(译) | 2020 | 国际品牌观察2020，0，1： | 0 |
| 9 | Diverse perennial circular forage systems are needed to foster resilience, ecosystem services, and socioeconomic benefits in agricultural landscapes显示文摘Prevailing agricultural systems dominated by annual crop monocultures,and the landscapes that contain them,lack resilience and multifunctionality.They are vulnerable to extreme weather events,contribute to degradation of soil,water,and air quality,reduce biodiversity,and negatively impact human health,social engagement,and equity.To achieve greater resilience,stability,and multiple ecosystem services therein,and to improve socioeconomic outcomes,we propose a practical framework to gain multifunctionality at multiple scales.This framework includes forages within agroecosystems that have the essential structural features of diversity,perenniality,and circularity.These three structural features are associated with increased resilience,stability,and provision of several ecosystem services,which in turn improve human health and socioeconomic outcomes.This framework improves understanding of,and access to,tools and materials for promoting the adoption of diverse circular agroecosystems with perennial forages.Application of this framework can result in land transformations that solve sustainability challenges in agriculture if policy,economic,and social barriers can be overcome by a transdisciplinary process of equitable knowledge production. | Valentin D.Picasso Marisol Berti Kim Cassida Sarah Collier Di Fang Ann Finan Margaret Krome David Hannaway William Lamp Andrew W.Stevens Carol Williams | 2022 | Grassland Research2022，1，2： | 0 |
| 10 | Joint Multi-modal Parcellation of the Human Striatum:Functions and Clinical Relevance显示文摘The human striatum is essential for both lowand high-level functions and has been implicated in the pathophysiology of various prevalent disorders,including Parkinson's disease(PD)and schizophrenia(SCZ).It is known to consist of structurally and functionally divergent subdivisions.However,previous parcellations are based on a single neuroimaging modality,leaving the extent of the multi-modal organization of the striatum unknown.Here,we investigated the organization of the striatum across three modalities—resting-state functional connectivity,probabilistic diffusion tractography,and structural covariance—to provide a holistic convergent view of its structure and function.We found convergent clusters in the dorsal,dorsolateral,rostral,ventral,and caudal striatum.Functional characterization revealed the anterior striatum to be mainly associated with cognitive and emotional functions,while the caudal striatum was related to action execution.Interestingly,significant structural atrophy in the rostral and ventral striatum was common to both PD and SCZ,but atrophy in the dorsolateral striatum was specifically attributable to PD.Our study revealed a cross-modal convergent organization of the striatum,representing a fundamental topographical model that can be useful for investigating structural and functional variability in aging and in clinical conditions. | Xiaojin Liu Simon B.Eickhoff Felix Hoffstaedter Sarah Genon Svenja Caspers Kathrin Reetz Imis Dogan Claudia R.Eickhoff Ji Chen Julian Caspers Niels Reuter Christian Mathys Andre Aleman Renaud Jardri Valentin Riedl Iris E.Sommer Kaustubh R.Patil | 2020 | Neuroscience Bulletin2020，36，10： | 0 |
| 11 | Identifying associations between epidemiological entities in news data for animal disease surveillance显示文摘Event-based surveillance systems are at the crossroads of human and animal(and plant and ecosystem)health,epidemiology,statistics,and informatics.Thus,their deployment faces many challenges specific to each domain and their intersections,such as relations among automation,artificial intelligence,and expertise.In this context,ourwork pertins to the extraction of epidemiological events in textual data(i.e.news)by unsupervised methods.We define the event extraction task as detecting pairs of epidemiological entities(e.g.a disease name and location).The quality of the ranked lists of pairs was evaluated using specific ranking evaluation metrics.We used a publicly available annotated corpus of 438 documents(i.e.news articles)related to animal disease events.The statistical approach was able to detect event-related pairs of epidemiological features with a good trade-off between precision and recall.Our results showed that using a window of words outperformed document-based and sentence-based approaches,while reducing the probability of detecting false pairs.Our results indicated that Mutual Information was less adapted than the Dice coefficient for ranking pairs of features in the event extraction framework.We believe that Mutual Information would be more relevant for rare pair detection(i.e.weak signals),but requires higher manual curation to avoid false positive extraction pairs.Moreover,generalising the country-level spatial features enabled better discrimination(i.e.ranking)of relevant disease-location pairs for event extraction. | Sarah Valentin Renaud Lancelot Mathieu Roche | 2021 | Artificial Intelligence in Agriculture2021，，1： | 0 |
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