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Large-scale transcriptomics data studies revolutionised the fields of systems biology and medicine, allowing to generate deeper mechanistic insights into biological pathways and molecular functions. However, conventional bulk RNA-sequencing results in the analysis of an averaged signal of many input cells, which are homogenised during the experimental procedure. Hence, those insights represent only a coarse-grained picture, potentially missing information from rare or unidentified cell types. Allowing for an unprecedented level of resolution, single-cell transcriptomics may help to identify and characterise new cell types, unravel developmental trajectories, and facilitate inference of cell type-specific networks. Besides all these tempting promises, there is one main limitation that currently hampers many downstream tasks: single-cell RNA-sequencing data is characterised by a high degree of sparsity. Due to this limitation, no reliable network inference tools allowed to disentangle the hidden information in the single-cell data. Single-cell correlation networks likely hold previously masked information and could allow inferring new insights into cell type-specific networks. To harness the potential of single-cell transcriptomics data, this dissertation sought to evaluate the influence of data dropout on network inference and how this might be alleviated. However, two premisses must be met to fulfil the promise of cell type-specific networks: (I) cell type annotation and (II) reliable network inference. Since any experimentally generated scRNA-seq data is associated with an unknown degree of dropout, a benchmarking framework was set up using a synthetic gold data set, which was subsequently affected with different defined degrees of dropout. Aiming to desparsify the dropout-afflicted data, the influence of various imputations tools on the network structure was further evaluated. The results highlighted that for moderate dropout levels, a deep count autoencoder (DCA) was able to outperform the other tools and the unimputed data. To fulfil the premiss of cell type annotation, the impact of data imputation on cell-cell correlations was investigated using a human retina organoid data set. The results highlighted that no imputation tool intervened with cell cluster annotation. Based on the encouraging results of the benchmarking analysis, a window of opportunity was identified, which allowed for meaningful network inference from imputed single-cell RNA-seq data. Therefore, the inference of cell type-specific networks subsequent to DCA-imputation was evaluated in a human retina organoid data set. To understand the differences and commonalities of cell type-specific networks, those were analysed for cones and rods, two closely related photoreceptor cell types of the retina. Comparing the importance of marker genes for rods and cones between their respective cell type-specific networks exhibited that these genes were of high importance, i.e. had hub-gene-like properties in one module of the corresponding network but were of less importance in the opposing network. Furthermore, it was analysed how many hub genes in general preserved their status across cell type-specific networks and whether they associate with similar or diverging sub-networks. While a set of preserved hub genes was identified, a few were linked to completely different network structures. One candidate was EIF4EBP1, a eukaryotic translation initiation factor binding protein, which is associated with a retinal pathology called age-related macular degeneration (AMD). These results suggest that given very defined prerequisites, data imputation via DCA can indeed facilitate cell type-specific network inference, delivering promising biological insights. Referring back to AMD, a major cause for the loss of central vision in patients older than 65, neither the defined mechanisms of pathogenesis nor treatment options are at hand. However, light can be shed on this disease through the employment of organoid model systems since they resemble the in vivo organ composition while reducing its complexity and ethical concerns. Therefore, a recently developed human retina organoid system (HRO) was investigated using the single-cell toolbox to evaluate whether it provides a useful base to study the defined effects on the onset and progression of AMD in the future. In particular, different workflows for a robust and in-depth annotation of cell types were used, including literature-based and transfer learning approaches. These allowed to state that the organoid system may reproduce hallmarks of a more central retina, which is an important determinant of AMD pathogenesis. Also, using trajectory analysis, it could be detected that the organoids in part reproduce major developmental hallmarks of the retina, but that different HRO samples exhibited developmental differences that point at different degrees of maturation. Altogether, this analysis allowed to deeply characterise a human retinal organoid system, which revealed in vivo-like outcomes and features as pinpointing discrepancies. These results could be used to refine culture conditions during the organoid differentiation to optimise its utility as a disease model. In summary, this dissertation describes a workflow that, in contrast to the current state of the art in the literature enables the inference of cell type-specific gene regulatory networks. The thesis illustrated that such networks indeed differ even between closely related cells. Thus, single-cell transcriptomics can yield unprecedented insights into so far not understood cell regulatory principles, particularly rare cell types that are so far hardly reflected in bulk-derived RNA-seq data.

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abstract: Network analysis is a key conceptual orientation and analytical tool in the social sciences that emphasizes the embeddedness of individual behavior within a larger web of social relations. The network approach is used to better understand the cause and consequence of social interactions which cannot be treated as independent. The relational nature of network data and models, however, amplify the methodological concerns associated with inaccurate or missing data. This dissertation addresses such concerns via three projects. As a motivating substantive example, Project 1 examines factors associated with the selection of interaction partners by students at a large urban high school implementing a reform which, like many organizational improvement initiatives, is associated with a theory of change that posits changes to the structuring of social interactions as a central causal pathway to improved outcomes. A distinctive aspect of the data used in Project 1 is that it was a complete egocentric network census – in addition to being asked about their own relationships, students were asked about the relationships between alters that they nominated in the self-report. This enables two unique examinations of methodological challenges in network survey data collection: Project 2 examines the factors related to how well survey respondents assess the strength of social connections between others, finding that "informant" competence corresponds positively with their social proximity to target dyad as well as their centrality in the network. Project 3 explores using such third-party reports to augment network imputation methods, and finds that incorporating third-party reports into model-based methods provides a significant boost in imputation accuracy. Together these findings provide important implications for collecting and extrapolating data in research contexts where a complete social network census is highly desirable but infeasible. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics for the Life and Social Sciences 2019

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京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第20427号 / 農博第2212号 / 新制||農||1048(附属図書館) / 学位論文||H29||N5048(農学部図書室) / 京都大学大学院農学研究科応用生物科学専攻 / (主査)准教授 谷口 幸雄, 教授 今井 裕, 教授 廣岡 博之 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

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Die Arbeit stellt sich die Frage nach den Preiseffekten großer Wohnungsportfoliotransaktionen auf das allgemeine Preisniveau am Markt für Bestandswohnungen in Mehrfamilienhäusern (MFH). Hintergrund der Fragestellung sind zahlreiche solcher Transaktionen seit den 2000er Jahren sowie die kritischen Stimmen zu diesem Geschehen in der Öffentlichkeit und den Medien, die den Zusammenhang zu steigenden Kauf- und Mietpreisen in diesem so wichtigen Segment großstädtischer Wohnungsmärkte postulieren. Hier setzt die Arbeit, mittels geeigneter Datengrundlage und mittels geeigneter Methodik, an, um für 17 großstädtische Wohnungsmärkte die Forschungsfrage zu Preiseffekten großer Wohnungsportfoliotransaktionen auf das Kaufpreisniveau von MFH-Bestandswohnungen zu beantworten. Dabei wird die Preisentwicklung im Untersuchungssegment der einzelnen Standorte, im Rahmen des gewöhnlichen Geschäftsverkehrs, anhand lokaler, hedonischer Preisindizes dem Stattfinden außergewöhnlicher Transaktionsereignisse in Form großer MFH-Bestandswohnungsportfolios gegenübergestellt und analysiert. Mit insgesamt 2,55 Mio. Wohnungen umfassen die untersuchten Märkte zum Stand 2011 6,3 % des deutschen Gesamtwohnungsbestandes, und mit 2,49 Mio. Bestandswohnungen (Baujahr vor 2005) sowie einem durchschnittlich 79,3 %igen MFH-Anteil weisen sie mit geschätzten 1,975 Mio. Wohnungen im MFH-Bestand einen Anteil von 9,23 % am spezifischen Marktsegment Gesamtdeutschlands auf. Die Marktauswahl stützt sich auf eine Datenanfrage an 78 deutsche Gutachterausschüsse aller kreisfreien Großstädte bzw. großstädtischer Stadtkreise. Im Ergebnis der Datenbereitstellung wurden für 17 dieser Märkte (rund 22 %) auf Basis der lokalen Kaufpreissammlung, für 44 Quartale im Zeitraum Q1:1998 bis Q4:2008 reale Transaktionsfälle des gewöhnlichen Geschäftsverkehrs ausgewertet. Die Untersuchungsmärkte repräsentieren dabei nach gängiger Typisierung alle Marktausprägungen gut. Insgesamt wurden ca. 110.000 bereinigte Datensätze des gewöhnlichen Transaktionsgeschehens für die Ableitung lokaler, hedonischer Kaufpreisindizes sowie deren nachfolgender Analyse berücksichtigt. Theoretisch stützt sich die Arbeit auf das wissenschaftlich anerkannte Immobilienmarktmodell von DiPasquale und Wheaton. Methodisch greift sowohl die Ableitung der Kaufpreisindizes für den gewöhnlichen Geschäftsverkehr auf Basis des hedonischen Ansatzes, als auch die panelökonometrische Analyse mittels fixed-effects-Modell den Stand der Forschung auf. Die vorliegende Arbeit liefert damit einerseits theoretisch und methodisch fundierte sowie empirisch belegte Erkenntnisse zur aktuellen und gesellschaftlich relevanten Frage der Preisentwicklung an großstädtischen Wohnungsmärkten, leitet andererseits aber aus ihren theoretischen und methodischen Arbeitsschritten auch wichtige Erkenntnisse und Empfehlungen für die laufende Wohnungsmarktbeobachtung ab.

This thesis examines the relationship between gestational age and stillbirths, focusing on the effect of maternal age. Prolonged pregnancies have been associated with an increased risk of stillbirth, prompting the exploration of labor induction as a preventive measure. However, the existing literature suffers from limited sample sizes, leading to uncertainty in the findings.  This study utilizes regional variations in labor induction practices to in- crease the sample size substantially. Moreover, it incorporates the economical aspect by evaluating the cost of induction and how the current policy could be optimized. In Sweden, some regions modified their induction policies in 2019 while others did not, creating a quasi-experimental setting that is exploited in this thesis. The objective is to evaluate the impact of inducing labor before pregnancies are defined as prolonged on stillbirth rates. A panel from 2009 to 2021, comprising over 1.4 million laborers, is analyzed, focusing on approximately 13,500 prolonged pregnancies between 2019 and 2021.  The results suggest that implementing a new induction policy among mothers aged 30 or older would yield annual cost savings of 24.6 MSEK. Specifically, targeting this age group for induction reduces the number of inductions required in week 41 to prevent one stillbirth from 224 to 127, compared to inducing mothers of all ages. These findings contribute to understanding labor induction practices and their impact on stillbirth rates, especially how the current policy could be optimized from a monetary perspective, providing valuable insights to policymakers.

Unintended pregnancies resulted in $21 billion in avoidable health care costs in the United States as of the most recently available data in 2010 and are associated with myriad negative health effects for mothers and children. They disparately impact vulnerable groups of women, such as those 18-29 years old, Black women, low-income women, single women, and less educated women. A medication abortion is one method of terminating a pregnancy which is over 95% effective, safe (with major adverse events in less than 0.5% of cases), has minor side effects, and costs less than 20% of a live birth.However, states have different levels of medication abortion utilization: in 2020, percentages ranged from 13.7% in Missouri to 96.6% in Wyoming in 2020. The FDA’s abortifacient protocol is more restrictive than medically necessary to ensure women’s safety. For example, although the FDA expanded medication abortions for use up to ten weeks of gestation in 2016 from the previous seven-week limit, studies show safety and efficacy beyond ten weeks of gestation. Many states have laws which restrict access to medication abortions beyond their laws that restrict access to all abortions. Additionally, many states have laws that regulate access to medication abortions more strictly than the FDA. These laws can result in a delay in obtaining abortion care, possibly past the FDA’s ten-week limit for medication abortions, which could make the patient ineligible for a medication abortion in some states. A state’s percentage of medication abortion utilization may depend upon which law(s) that state has in place restricting access. This is the first study to examine that relationship. There is a gap in the literature as to why medication abortion is underutilized given that a majority of abortions occur within the FDA’s ten-week time limit and that the majority of women who received an abortion would have preferred to receive it earlier than they did. The goal of this dissertation is to examine the impact of certain laws restricting medication abortion access on medication abortion utilization in states with such laws in place as compared to states without such laws in place. The aims of the proposed dissertation were threefold. Study one examined medication abortion utilization among women who obtained abortions in states with laws that restrict public and/or private insurance coverage of abortion as compared to states with no insurance coverage restrictions from 2010 to 2019. It was expected that restricting public and/or private insurance coverage of abortion would be statistically significantly associated with lower state medication abortion utilization as compared to states without public and/or private insurance coverage restrictions. Study two examined medication abortion utilization among women who obtained abortions in states that required both in-person physician involvement prior to the abortion and that the first dose be administered in person in the presence of a physician and states with only one physician involvement requirement as compared to states with neither physician involvement requirement from 2010 to 2019. It was expected that state laws requiring either or both in-person physician involvement prior to the abortion and/or that the first dose be administered in the presence of a physician will be statistically significantly associated with lower medication abortion utilization as compared to states requiring no in-person physician involvement. Study three examined medication abortion utilization among women who obtained abortions in states that require both in-person physician involvement prior to the abortion and that the first dose be administered in person in the presence of a physician and states with only one physician involvement requirement as compared to states with neither physician involvement requirement, adjusting for the percentage of women aged 15-44 living in counties without an abortion provider in 2017. It was expected that state laws requiring either or both in-person physician involvement prior to the abortion and/or that the first dose be administered in the presence of a physician would be statistically significantly associated with lower medication abortion utilization as compared to states requiring no in-person physician involvement, adjusting for the percentage of women aged 15-44 living in counties without an abortion provider in 2017. We used multiple imputation of data in all three of our studies, linear mixed model analyses in the first two, and a regression analysis in the third. While our studies did not uncover any statistically significant associations between the laws examined alone and medication abortion utilization, there were some statistically significant secondary findings. All three of our studies found states with higher percentages of patients who were at least ten weeks pregnant at the time of their abortions to be associated with lower percentages of medication abortion utilization. Our first study found that having had no previous live births was associated with a higher percentage of medication abortion utilization in states with laws restricting Health Exchange insurance plans from covering abortions, regardless of whether there were other laws restricting insurance coverage of abortion in place. Both our first and second studies found that being over thirty years of age at the time of obtaining an abortion was associated with a higher percentage of medication abortion utilization in states with at least one form of abortion insurance coverage restriction law and regardless of how many in-person physician interactions were required, respectively. These findings should guide both future research aimed at taking further steps toward understanding states’ disparate levels of medication abortion utilization as well as policymakers’ efforts at improving access to medication abortion services. / Public Health