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Importance: Predictors consistently associated with psychosis liability and course of illness in schizophrenia (SCZ) spectrum disorders (SSD), including the need for clozapine treatment, are lacking. Longitudinally ascertained medication use may empower studies examining associations between polygenic risk scores (PRSs) and pharmacotherapy choices. Objective: To examine associations between PRS-SCZ loading and groups with different liabilities to SSD (individuals with SSD taking clozapine, individuals with SSD taking other antipsychotics, their parents and siblings, and unrelated healthy controls) and between PRS-SCZ and the likelihood of receiving a prescription of clozapine relative to other antipsychotics. Design, Setting, and Participants: This genetic association study was a multicenter, observational cohort study with 6 years of follow-up. Included were individuals diagnosed with SSD who were taking clozapine or other antipsychotics, their parents and siblings, and unrelated healthy controls. Data were collected from 2004 until 2021 and analyzed between October 2021 and September 2022. Exposures: Polygenic risk scores for SCZ. Main Outcomes and Measures: Multinomial logistic regression was used to examine possible differences between groups by computing risk ratios (RRs), ie, ratios of the probability of pertaining to a particular group divided by the probability of healthy control status. We also computed PRS-informed odd ratios (ORs) for clozapine use relative to other antipsychotics. Results: Polygenic risk scores for SCZ were generated for 2344 participants (mean [SD] age, 36.95 years [14.38]; 994 female individuals [42.4%]) who remained after quality control screening (557 individuals with SSD taking clozapine, 350 individuals with SSD taking other antipsychotics during the 6-year follow-up, 542 parents and 574 siblings of individuals with SSD, and 321 unrelated healthy controls). All RR

Clozapine is the most effective antipsychotic for patients with treatment-resistant schizophrenia. However, response is highly variable and possible genetic underpinnings of this variability remain unknown. Here, we performed polygenic risk score (PRS) analyses to estimate the amount of variance in symptom severity among clozapine-treated patients explained by PRSs (R2) and examined the association between symptom severity and genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activity. Genome-wide association (GWA) analyses were performed to explore loci associated with symptom severity. A multicenter cohort of 804 patients (after quality control N = 684) with schizophrenia spectrum disorder treated with clozapine were cross-sectionally assessed using the Positive and Negative Syndrome Scale and/or the Clinical Global Impression-Severity (CGI-S) scale. GWA and PRS regression analyses were conducted. Genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activities were calculated. Schizophrenia-PRS was most significantly and positively associated with low symptom severity (p = 1.03 × 10-3; R2 = 1.85). Cross-disorder-PRS was also positively associated with lower CGI-S score (p = 0.01; R2 = 0.81). Compared to the lowest tertile, patients in the highest schizophrenia-PRS tertile had 1.94 times (p = 6.84×10-4) increased probability of low symptom severity. Higher genotype-predicted CYP2C19 enzyme activity was independently associated with lower symptom severity (p = 8.44×10-3). While no locus surpassed the genome-wide significance threshold, rs1923778 within NFIB showed a suggestive association (p = 3.78×10-7) with symptom severity. We show that high schizophrenia-PRS and genotype-predicted CYP2C19 enzyme activity are independently associated with lower symptom severity among individuals treated with clozapine. Our findings open avenues for future pharmacogenomic projects investigating the potential of PRS and genotype-predicted CYP-activity in schizophrenia.

Civil Engineering and Geosciences, Structural Engineering, Construction Management and Engineering

Tasks performed by intellectual property specialists are often ad hoc, and continuously require new approaches to search a collection of documents. We therefore investigate the benets of a visual `search strategy builder' to allow IP search experts to express their approach to searching the patent collection, without requiring IR or database expertise. These search strategies are executed on our probabilistic relational database framework. Search by strategy design can be very eective. We rened our search strategies after our initial submission to the CLEF-IP track, and with minor eort we could include techniques shown to be benecial for other CLEF-IP participants.

We investigate how a user-centred design to search can improve the support of user tasks specific to journalism. Illustrated by example information needs, sampled from our own exploration of the New York Times annotated corpus, we demonstrate how domain specific notions rooted in a field theory of journalism can be transformed into effective search strategies. We present a method for search-context aware classification of authorities, witnesses, reporters and columnists. A first search strategy supports the journalistic task of investigating the trustworthiness of a news source, whereas the second search strategy supports assessments of the objectivity of an author. In principle, these strategies can exploit the semantic annotations the corpus; however, based on our preliminary work with the corpus, we conclude that straightforward full-text search is still a crucial component of any effective search strategy, as only recent articles are annotated, and annotations are far from complete.

This paper describes a novel, XML-based approach towards managing and querying forensic traces extracted from digital evidence. This approach has been implemented in XIRAF, a prototype system for forensic analysis. XIRAF systematically applies forensic analysis tools to evidence files (e.g., hard disk images). Each tool produces structured XML annotations that can refer to regions (byte ranges) in an evidence file. XIRAF stores such annotations in an XML database, which allows us to query the annotations using a single, powerful query language (XQuery). XIRAF provides the forensic investigator with a rich query environment in which browsing, searching, and pre-defined query templates are all expressed in terms of XML database queries.

XML annotations are a widely occurring phenomenon in many application fields, and XML databases should be used to store and query such data. To provide intuitive and fast querying of annotations, we make a case for extending XPath with four new axis steps, that correspond with socalled StandOff joins, introduced here. The new steps can be efficiently implemented using a region index and fast looplifted StandOff MergeJoin algorithms. These techniques were added to the open-source XML DBMS MonetDB/XQuery, and we show in our evaluation it thus becomes capable of interactively querying >GB annotation databases.

This paper describes our approach to representing and querying multi-dimensional, possibly overlapping text annotations, as used in our question answering (QA) system. We use a system extending XQuery, the W3C-standard XML query language, with new axes that allow one to jump easily between different annotations of the same data. The new axes are formulated in terms of (partial) overlap and containment. All annotations are made using stand-off XML in a single document, which can be efficiently queried using the XQuery extension. The system is scalable to gigabytes of XML annotations. We show examples of the system in QA scenarios.