Time since liver transplant and immunosuppression withdrawal outcomes: Systematic review and individual patient data meta-analysis

Background & Aims Successful immunosuppression withdrawal (ISW) is possible for a subfraction of liver transplant (LT) recipients but the factors that define the risk of ISW failure are largely unknown. One candidate prognostic factor for ISW success or operational tolerance (OT) is longer time between LT and ISW which we term “pre-withdrawal time”. To clarify the impact of pre-withdrawal time span on subsequent ISW success or failure, we conducted a systematic review with meta-analysis. Methods We systematically interrogated the literature for LT recipient ISW studies reporting pre-withdrawal time. Eligible articles from Embase, Medline, and the Cochrane Central Register of Controlled Trials were used for backward and forward citation searching. Pre-withdrawal time individual patient data (IPD) was requested from authors. Pooled mean differences and time-response curves were calculated using random-effects meta-analyses. Results We included 17 studies with 691 patients, 15 of which (620 patients) with IPD. Study-level risk of bias was heterogeneous. Mean pre-withdrawal time was greater by 427 days [95% confidence interval (CI) 67–788] in OT compared to non-OT patients. This increase was potentiated to 799 days (95% CI 369–1229) or 1074 days (95% CI 685–1463) when restricting analysis to adult or European study participants. In time-response meta-analysis for adult or European ISW candidates, likelihood of OT increased by 7% (95% CI 4–10%) per year after LT (GRADE low- and moderate-certainty of evidence, respectively). Conclusions Our data support the impact of pre-withdrawal time in ISW decision-making for adult and European LT recipients. PROSPERO REGISTRATION: CRD42021272995

Quartier und Nachbarschaft machen: eine stadtethnographische Untersuchung in Basel über (Re-)Produktionen lokaler Räume und Sozialitäten

Mit ethnographischen Methoden erkundet die Autorin ausgehend von Basel die Praxen unterschiedlicher, vor allem kollektiver Akteur*innen, die sich auf die Konzepte Quartier und Nachbarschaft beziehen und dadurch zugleich auch Quartier und Nachbarschaft, Quartierbewohnende und Nachbar*innen machen. Sie beschäftigt sich unter anderem mit Mitwirkungsverfahren, Vereinen und Apps, die gezielt Nachbar*innen miteinander bekannt machen, oder einer Bewegung, die durch die Entwicklung multifunktionaler Nachbarschaften einen sozio-ökologischen Wandel herbeiführen will. Die Untersuchung macht deutlich, dass Quartier und Nachbarschaft als lokale Räume und Sozialitäten in gegenwärtigen Kontexten translokaler Vernetzung und umfassender Mediatisierung keineswegs an Bedeutung verlieren, sondern von verschiedensten Akteur*innen als Bezugs- und Orientierungspunkte genutzt und dabei immer wieder neu und anders versammelt, imaginiert, praktiziert und (re-)produziert werden

Sparse grid approximation of the Riccati equation

In this article, we study the sparse grid discretization for the numerical solution of the algebraic Riccati equation (ARE). This approach is of particular interest for the solution of large scale AREs. Such AREs arise, for example, from the discretization of the operator Riccati equations associated with the linear quadratic control of systems evolving in a Hilbert space $H$. Following [4, 45], we formulate the ARE as a nonlinear operator equation on the space of Hilbert–Schmidt operators and derive the matrix equation for the sparse grid discretization. Provided that $O(N)$ degrees of freedom are used to discretize the space $H$, the sparse grid approximation of the ARE requires $O(N \log N)$ degrees of freedom. Especially, we propose an algorithm that evaluates the approximated ARE with $O(N^{3/2})$ operations. This considerably reduces the cost of solving the ARE compared to the $O(N^2)$ memory requirement and $O(N^3)$ complexity of the regular tensor product discretization. Numerical results are presented to validate the approach

Applications of deep learning in biology

The rapid growth of biological data sets has created a pressing need for powerful compu- tational tools to analyze and interpret this data. Deep learning, a subfield of artificial intelli- gence, has emerged as a promising approach for tackling this challenge. In this thesis, the applications of deep learning in biology, mainly focussing on image analysis and predicting protein-protein interaction are explored. I describe the basic components of deep learning models, including convolutional neural networks and modern attention-based networks, and discuss their potential for analyzing complex biological data sets. I also examine the chal- lenges of integrating and applying deep learning in a biomedical context, including issues of data quality, model interpretability, and ethical considerations. Overall, this thesis highlights the exciting potential of deep learning to transform the field of biological research and provides a roadmap for future applications in this rapidly evolving field

Depression trajectories during the COVID-19 pandemic in the high-quality health care setting of Switzerland: the COVCO-Basel cohort

OBJECTIVES: During the pandemic, Switzerland avoided stringent lockdowns and provided funds to stabilize the economy. To assess whether and in what subgroups the pandemic impacted on depressive symptoms in this specific Swiss context, we derived depression trajectories over an extended pandemic period in a Swiss cohort and related them to individuals' sociodemographic characteristics. STUDY DESIGN: This was a population-based cohort study. METHODS: The population-based COVCO-Basel cohort in North-Western Switzerland invited 112,848 adult residents of whom 12,724 participated at baseline. Between July 2020 and December 2021, 6396 participants answered to additional 18 monthly online questionnaires. Depression symptoms were repeatedly measured by the DASS-21 scale. Group-based Trajectory Models methods were applied to identify clusters of similar depression trajectories. Trajectory clusters were characterized descriptively and with a Multinomial response model. RESULTS: Three distinct trajectories were identified. The 'Highly affected' trajectory (13%) had a larger presence of younger and female participants with lower average income, higher levels of past depression, and living alone. A majority of individuals in the 'Unaffected' trajectory (52%) were of medium or high average income, older average age, without previous depression symptoms, and not living alone. The 'Moderately affected' trajectory (35%) had a composition intermediate between the two opposite 'extreme' trajectories. CONCLUSIONS: This study is among few studies investigating depression trajectories up to the time when COVID-19 vaccination was readily available to the entire population. During these 18 months of the pandemic, depressive symptoms increased in a substantial percentage of participants. Economic support, high-quality health care system, and moderate containment measures did not sufficiently protect all population subgroups from adverse, potentially long-term psychological pandemic impacts

Materials perspectives on achieving pyrochlore-based quantum spin liquid ground states

Exotic magnetic systems often stem from frustration caused by competing interactions. The epitome of magnetically frustrated system is incarnated by the quantum spin liquids. These systems are expected to evade magnetic ordering or freezing down to absolute zero Temperature. Magnetic correlations are expected to be strong and can lead to quantum entanglement over large scales as well as the emergence of exotic excitations. Stabilizing such a phase in a rare-earth pyrochlore oxide yields a so-called quantum spin ice resulting from the coherent superposition of ‘two-in-two-out’ spin ice configurations, reminiscent of the arrangement of hydrogen atoms in water ice. In some rare-earth pyrochlore oxides, magnetic rare earth ions experience a strong uniaxial anisotropy as well as frustrated ferromagnetic interactions, two of the main ingredients stabilizing a spin ice state. In particular, Ho2Ti2O7 and Dy2Ti2O7 have been thoroughly studied and are now two well established examples of classical spin ices. Owing to a reduced dipolar interaction, similar materials hosting smaller magnetic moments are thought to be ideal systems to search for quantum spin ices states. Such a state is favored by an Hamiltonian composed of a leading but not exceedingly large Ising term, forming the ’ice’ state, accompanied by smaller but non-negligible transverse terms allowing quantum fluctuations to tunnel through equivalent spin ice configurations. Additionally, other properties such as multipolar degrees of freedom, structural disorder or low-lying crystal-electric field levels are expected to have significant contributions to the magnetic ground state. Cerium-based pyrochlores are promising quantum spin liquids candidates, which received little attention until recently due to their demanding synthesis. Using thermodynamic measurements together with a detailed structural and crystal-electric field analysis, we show that both Ce2Sn2O7 and Ce2Hf2O7 display magnetic moments with an Ising character and no sign of spin ordering or freezing despite signs of magnetic correlations at low temperatures. Through various neutron experiments, we demonstrate that the compounds form a peculiar octupolar quantum spin ice state, where dominant octupolar correlations conspire to form a coherent ‘ice-like’ phase from which fractional excitations emerge. High resolution neutron backscattering spectroscopy shows convinc- ing agreement with the theoretical predictions of the quantum electrodynamics emerging from a quantum spin ice phase. Disorder is known to have a significant influence on spin liquids, typically leading to spin freezing or ordering. In particular, pyrochlore oxides containing non-Kramers rare earths are very sensitive to structural disorder, a specificity that was theoretically proposed as a way to stabilize a quantum spin liquid phase. We hereby present the study of three cases where structural disorder plays a prominent role in the low temperature magnetic properties. We start with the case of Tb2Hf2O7, a strongly disordered yet very promising spin liquid candidate with a puzzling low temperature correlated state. A detailed structural analysis, coupled with a point charge model, yields a qualitative understanding of the single-ion properties of this compound and provides new insights into the mechanisms behind its low temperature behavior. We then perform a comparative structural study of two praseodymium-based compounds, Pr2Hf2O7 and Pr2Zr2O7, which display distinct magnetic ground states in spite of their structural and chemical proximity. Finally, we show how the control over the structural disorder via chemical substitution allows the tuning of the magnetic behavior of spin ice state observed in Ho2Ti2O7

Determinanten von Stigmatisierung und der Akzeptanz von Zwangsmassnahmen in der Psychiatrie

Because they are viewed as violent, unpredictable, and dangerous, psychiatric patients experience a great deal of stigma. People with mental illnesses who are stigmatized may experience undesirable outcomes such social rejection, exclusion, and discrimination. The public's acceptance of coercion in psychiatry and the clinical use of coercion may be affected by this stigmatization, as well as the attitudes of medical professionals. The thesis sought to compare the extent of case-specific public acceptance of coercive measures in psychiatry and the impact of stigmatization (Steiger et al., 2021, study 1), investigate the relationships between the Big Five personality traits, self-esteem, and stigmatization (Steiger et al., 2022, study 2), and to compare the degree of case-specific approval of coercive measures in psychiatry by the public with the degree of general approval of coercive measures in psychiatry by the public. (Steiger et al., 2022, study 3). We conducted a representative survey of the general population (N = 2207) in the canton of Basel-City, Switzerland. Participants were asked to read a vignette depicting either the psychiatric symptoms of a fictitious character or a psychiatric service institution to which the character had been admitted. Regression analyses were employed to examine the associations between approval of coercive measures, desire for social distance, and perceived dangerousness (as indicators for stigmatization) with person - and situation-specific factors that influence stigmatization. The first study showed that the person in the case vignette exhibiting dangerous behavior, showing symptoms of a psychotic disorder, being perceived as dangerous, and treatment being understood as helpful increased approval of coercion in general, while familiarity of the respondents with mental illness decreased approval. The second study found associations between personality traits and stigmatization towards mental illness. Those who scored higher on openness to experience and agreeableness showed a lower desire for social distance and lower perceived dangerousness. Neuroticism was inversely associated with perceived dangerousness. Additionally, high self-esteem was positively associated with social distance and perceived dangerousness. Finally, perceived dangerousness partially mediated the association between desire for social distance and openness to experience as well as agreeableness. Study 3 found that assessment of case vignettes without dangerous behavior was associated with significantly reduced approval of coercion than assessment of a case vignette with dangerousness, while assessment of a psychiatric patient with dangerous behavior in general was connected with a significantly higher approval of coercion than assessment of a case vignette with dangerousness. Concluding, the three presented studies suggest that a considerable part of the approval for coercion is predicted by stigmatization. With the increasing severity of coercive measures, the influence of person- and situation-specific factors and of familiarity with mental illness decreased and generalizing and stigmatizing attitudes became stronger predictors for the approval of more severe measures. Furthermore, the current thesis highlights the role of personality traits and selfesteem in areas of stigma. Finally, case-specific assessment seems to reduce approval for coercion, whereas generalized assessment seems to favor approval of coercive measures