Publications by authors named "D van Dijk"

506 Publications

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics.

Proc Mach Learn Res 2020 07;119:9526-9536

Department of Computer Science, Yale University, New Haven, CT, USA.

It is increasingly common to encounter data from dynamic processes captured by static cross-sectional measurements over time, particularly in biomedical settings. Recent attempts to model individual trajectories from this data use optimal transport to create pairwise matchings between time points. However, these methods cannot model continuous dynamics and non-linear paths that entities can take in these systems. To address this issue, we establish a link between continuous normalizing flows and dynamic optimal transport, that allows us to model the expected paths of points over time. Continuous normalizing flows are generally under constrained, as they are allowed to take an arbitrary path from the source to the target distribution. We present , which controls the continuous paths taken between distributions to produce dynamic optimal transport. We show how this is particularly applicable for studying cellular dynamics in data from single-cell RNA sequencing (scRNA-seq) technologies, and that TrajectoryNet improves upon recently proposed static optimal transport-based models that can be used for interpolating cellular distributions.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8320749PMC
July 2020

Generating hard-to-obtain information from easy-to-obtain information: Applications in drug discovery and clinical inference.

Patterns (N Y) 2021 Jul 17;2(7):100288. Epub 2021 Jun 17.

Department of Computer Science, Yale University, New Haven, CT, USA.

Often when biological entities are measured in multiple ways, there are distinct categories of information: some information is easy-to-obtain information (EI) and can be gathered on virtually every subject of interest, while other information is hard-to-obtain information (HI) and can only be gathered on some. We propose building a model to make probabilistic predictions of HI using EI. Our feature mapping GAN (FMGAN), based on the conditional GAN framework, uses an embedding network to process conditions as part of the conditional GAN training to create manifold structure when it is not readily present in the conditions. We experiment on generating RNA sequencing of cell lines perturbed with a drug conditioned on the drug's chemical structure and generating FACS data from clinical monitoring variables on a cohort of COVID-19 patients, effectively describing their immune response in great detail.
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http://dx.doi.org/10.1016/j.patter.2021.100288DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276014PMC
July 2021

Response to Letter to the Editor from Laidlaw: "Erythrocytosis in a Large Cohort of Trans Men Using Testosterone: A Long-Term Follow-Up Study on Prevalence, Determinants, and Exposure Years".

J Clin Endocrinol Metab 2021 Jul 20. Epub 2021 Jul 20.

Department of Endocrinology and Center of Expertise on Gender Dysphoria, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.

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http://dx.doi.org/10.1210/clinem/dgab515DOI Listing
July 2021

Impact of Comorbid Personality Disorders on Depression Treatment in Routine Outpatient Care.

Am J Psychother 2021 Jun 17:appipsychotherapy20200046. Epub 2021 Jun 17.

Department of Clinical Psychological Science, Maastricht University, ​Maastrich, the Netherlands (van Bronswijk, van Dijk, Peeters); Department of Psychiatry and Psychology, Maastricht University Medical Center+, Maastricht, the Netherlands (van Bronswijk); Department of Mood Disorders, PsyQ Haaglanden, the Hague, the Netherlands (van Dijk, van den Boogaard); Parnassia Psychiatric Institute, the Hague (Deen); Institute of Psychology, Leiden University, Leiden, the Netherlands (Deen); Department of Psychiatry, Radboud University Medical Center, Nijmegen, the Netherlands (Ruhé); Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen (Ruhé); Pro Persona Mental Healthcare, and Behavourial Science Institute, Radboud University, Nijmegen (Spijker).

Objective: The impact of personality disorder on treatment effectiveness for depression has been debated, and study results have been inconsistent. However, studies that report a negative impact of personality disorders on depression treatment outcomes are often characterized by uncontrolled treatment designs. Within such contexts, individuals with depression and personality disorders are at risk to receive suboptimal treatment. The aim of this retrospective observational study was to investigate whether and to what extent comorbid personality disorders were associated with the type and amount of depression treatment received in routine outpatient care.

Methods: Retrospectively extracted data from electronic records of 1,455 outpatients treated for depression at several sites of a nationwide mental health provider in the Netherlands were included. The type and number of treatment sessions and visits were analyzed by using regression models.

Results: Individuals with depression and comorbid personality disorders received more psychotherapy sessions than individuals without personality disorders, irrespective of depression severity. The number of pharmacotherapy sessions and supportive and crisis visits did not differ between individuals with and without comorbid personality disorders.

Conclusions: Individuals with depression and personality disorders received more intensive treatment than individuals without comorbid personality disorders. These results conflict with treatment guidelines and recommendations from high-quality studies and may be indicative of overtreatment among this large group of patients.
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http://dx.doi.org/10.1176/appi.psychotherapy.20200046DOI Listing
June 2021

A trouble shared is a trouble halved: The role of family identification and identification with humankind in well-being during the COVID-19 pandemic.

Br J Soc Psychol 2021 Jun 16. Epub 2021 Jun 16.

Department of Social Psychology, Goethe University Frankfurt, Germany.

The COVID-19 pandemic has triggered health-related anxiety in ways that undermine peoples' mental and physical health. Contextual factors such as living in a high-risk area might further increase the risk of health deterioration. Based on the Social Identity Approach, we argue that social identities can not only be local that are characterized by social interactions, but also be global that are characterized by a symbolic sense of togetherness and that both of these can be a basis for health. In line with these ideas, we tested how identification with one's family and with humankind relates to stress and physical symptoms while experiencing health-related anxiety and being exposed to contextual risk factors. We tested our assumptions in a representative sample (N = 974) two-wave survey study with a 4-week time lag. The results show that anxiety at Time 1 was positively related to stress and physical symptoms at Time 2. Feeling exposed to risk factors related to lower physical health, but was unrelated to stress. Family identification and identification with humankind were both negatively associated with subsequent stress and family identification was negatively associated with subsequent physical symptoms. These findings suggest that for social identities to be beneficial for mental health, they can be embodied as well as symbolic.
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http://dx.doi.org/10.1111/bjso.12470DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8420363PMC
June 2021
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