Second-position clitics and the syntax-phonology interface: The case of ancient Greek

In this paper we discuss second position clitics in ancient Greek, which show a remarkable ability to break up syntactic constituents. We argue against attempts to capture such data in terms of a mismatch between c-structure yield and surface string and instead propose to enrich c-structure by using a multiple context free grammar with explicit yield functions rather than an ordinary CFG

Hospital- and patient-related factors associated with differences in hospital antibiotic use: analysis of national surveillance results

Background Surveillance data of antibiotic use are increasingly being used for benchmarking purposes, but there is a lack of studies dealing with how hospital- and patient-related factors affect antibiotic utilization in hospitals. Our objective was to identify factors that may contribute to differences in antibiotic use. Methods Based on pharmacy sales data (2006–2011), use of all antibiotics, all penicillins, and broad-spectrum antibiotics was analysed in 22 Health Enterprises (HEs). Antibiotic utilization was measured in World Health Organisation defined daily doses (DDDs) and hospital-adjusted (ha)DDDs, each related to the number of bed days (BDs) and the number of discharges. For each HE, all clinical specialties were included and the aggregated data at the HE level constituted the basis for the analyses. Fourteen variables potentially associated with the observed antibiotic use – extracted from validated national databases – were examined in 12 multiple linear regression models, with four different measurement units: DDD/100 BDs, DDD/100 discharges, haDDD/100 BDs and haDDD/100 discharges. Results Six variables were independently associated with antibiotic use, but with a variable pattern depending on the regression model. High levels of nurse staffing, high proportions of short (10 days) hospital stays, infectious diseases being the main ICD-10 diagnostic codes, and surgical diagnosis-related groups were correlated with a high use of all antibiotics. University affiliated HEs had a lower level of antibiotic utilization than other institutions in eight of the 12 models, and carried a high explanatory strength. The use of broad-spectrum antibiotics correlated strongly with short and long hospital stays. There was a residual variance (30%–50% for all antibiotics; 60%–70% for broad-spectrum antibiotics) that our analysis did not explain. Conclusions The factors associated with hospital antibiotic use were mostly non-modifiable. By adjusting for these factors, it will be easier to evaluate and understand observed differences in antibiotic use between hospitals. Consequently, the inter-hospital differences can be more confidently acted upon. The residual variation is presumed to largely reflect prescriber-related factors

The anaphoric semantics of partial control

This paper deals with partial control, the phenomenon that instead of identity there is a subset relation between the controller and the controllee in a control construction. We argue that the context dependency of partial control requires an anaphoric approach, rather than hard-coding the possibility of a reference shift in the semantics of the control verb. The anaphoric analysis is formalized in Partial Compositional Discourse Representation Theory

Integrating LFG’s binding theory with PCDRT

We provide a formal model for the interaction of syntax and pragmatics in the interpretation of anaphoric binding constraints on personal and reflexive pronouns. We assume a dynamic semantics, where e-type expressions introduce discourse referents, and contexts are assignments of individuals to discourse referents. We adopt the Partial Compositional Discourse Representation Theory (PCDRT) of Haug (2014b),which models anaphoric resolution in terms of a pragmatically-established relation between discourse referents. We integrate PCDRT into the constraint-based grammatical framework of Lexical-Functional Grammar (LFG), and show how it is possible to state syntactic constraints on the pragmatic resolution of singular and plural anaphora within this framework

Hospital physicians' experiences with procalcitonin - implications for antimicrobial stewardship; a qualitative study.

Background. Procalcitonin is an inflammatory biomarker that is sensitive for bacterial infections and a promising clinical decision aid in antimicrobial stewardship programs. However, there are few studies of physicians’ experiences concerning the use of PCT. The objective of this study was to investigate whether hospital physicians’ experience with procalcitonin after 18 months of use can inform the PCT implementation in antimicrobial stewardship programs. Materials/methods. We deployed a qualitative approach using semi-structured interviews with 14 hospital physicians who had experience with procalcitonin in clinical practice. Interviews were audio-taped, transcribed verbatim and analysed using thematic analysis. Results. Physicians reported a knowledge gap, which made them uncertain about the appropriate procalcitonin use, interpretation, and trustworthiness. Simultaneously, the physicians experienced procalcitonin as a useful clinical decision aid but emphasised that their clinical evaluation of the patient was the most important factor when deciding on antibiotic treatment. Conclusions. Procalcitonin was regarded a helpful clinical tool, but the physicians called for more knowledge about its appropriate uses. Active implementation of unambiguous procalcitonin algorithms and physician education may enhance the utility of the test as an antimicrobial stewardship adjunct.publishedVersio

The Role of Procalcitonin as an Antimicrobial Stewardship Tool in Patients Hospitalized with Seasonal Influenza

Background: Up to 60% of the antibiotics prescribed to patients hospitalized with seasonal influenza are unnecessary. Procalcitonin (PCT) has the potential as an antimicrobial stewardship program (ASP) tool because it can differentiate between viral and bacterial etiology. We aimed to explore the role of PCT as an ASP tool in hospitalized seasonal influenza patients. Methods: We prospectively included 116 adults with seasonal influenza from two influenza seasons, 2018–2020. All data was obtained from a single clinical setting and analyzed by descriptive statistics and regression models. Results: In regression analyses, we found a positive association of PCT with 30 days mortality and the amount of antibiotics used. Influenza diagnosis was associated with less antibiotic use if the PCT value was low. Patients with a low initial PCT (<0.25 µg/L) had fewer hospital and intensive care unit (ICU) days and fewer positive chest X-rays. PCT had a negative predictive value of 94% for ICU care stay, 98% for 30 days mortality, and 88% for bacterial coinfection. Conclusion: PCT can be a safe rule-out test for bacterial coinfection. Routine PCT use in seasonal influenza patients with an uncertain clinical picture, and rapid influenza PCR testing, may be efficient as ASP tools.publishedVersio

How radiographers visually perceive X-ray images with the task of accepting or rejecting them – a pilot study

Introduction: Radiographer´s usual role in the medical imaging chain is to acquire relevant and qualitatively good images that help the radiologist or physician to diagnose most accurately. After the image acquisition, the radiographer does a quality evaluation based on established imaging criteria to decide if the image is satisfactory, or otherwise reject it and subsequently take a new one. Contrary to expectations that the number of image rejects should decrease substantially with the introduction of digital imaging, a number of studies have shown that it has not, although the reasons for rejects has changed from exposure errors to positioning and centring errors. Very little research has been on examining how radiographers visually perceive and evaluate the X-ray images in this acceptance/rejection process. Purpose: Investigate how radiographers and radiography students visually perceives X-ray images in the process of accepting or rejecting them on basis of radiographic imaging criteria, and see if there are differences in strategies across experience levels. Materials and methods: Three radiography students and five radiographers with varying years of experience were given the task of accepting or rejecting shoulder and knee projection images based on positioning criteria. Using eye tracking, we measured the participants’ number and duration of gaze fixations within 1) the field of view defined by the monitor display, 2) the part of the monitor displaying the X-ray image only, and 3) the region within the X-ray images considered to be most relevant given the imaging criteria task. The quantitative eye-tracking measurements were followed-up by four qualitative questions. Results: Some differences in fixation patterns between the groups were found; the medium experienced radiographers spent statistically significant lesser number of fixations and lesser average single fixation durations than both the radiography students and the most experienced radiographers did, whereas the two latter groups scored almost equally. Conclusion: The study revealed that work experience might have some influence on how radiographers and radiography students assess X-ray images, but in subtler ways than expected. The study also revealed, however, quite large individual differences across experience

ImmunoLingo: Linguistics-based formalization of the antibody language

Apparent parallels between natural language and biological sequence have led to a recent surge in the application of deep language models (LMs) to the analysis of antibody and other biological sequences. However, a lack of a rigorous linguistic formalization of biological sequence languages, which would define basic components, such as lexicon (i.e., the discrete units of the language) and grammar (i.e., the rules that link sequence well-formedness, structure, and meaning) has led to largely domain-unspecific applications of LMs, which do not take into account the underlying structure of the biological sequences studied. A linguistic formalization, on the other hand, establishes linguistically-informed and thus domain-adapted components for LM applications. It would facilitate a better understanding of how differences and similarities between natural language and biological sequences influence the quality of LMs, which is crucial for the design of interpretable models with extractable sequence-functions relationship rules, such as the ones underlying the antibody specificity prediction problem. Deciphering the rules of antibody specificity is crucial to accelerating rational and in silico biotherapeutic drug design. Here, we formalize the properties of the antibody language and thereby establish not only a foundation for the application of linguistic tools in adaptive immune receptor analysis but also for the systematic immunolinguistic studies of immune receptor specificity in general.Comment: 19 pages, 3 figure

Linguistically inspired roadmap for building biologically reliable protein language models

Deep neural-network-based language models (LMs) are increasingly applied to large-scale protein sequence data to predict protein function. However, being largely black-box models and thus challenging to interpret, current protein LM approaches do not contribute to a fundamental understanding of sequence-function mappings, hindering rule-based biotherapeutic drug development. We argue that guidance drawn from linguistics, a field specialized in analytical rule extraction from natural language data, can aid with building more interpretable protein LMs that are more likely to learn relevant domain-specific rules. Differences between protein sequence data and linguistic sequence data require the integration of more domain-specific knowledge in protein LMs compared to natural language LMs. Here, we provide a linguistics-based roadmap for protein LM pipeline choices with regard to training data, tokenization, token embedding, sequence embedding, and model interpretation. Incorporating linguistic ideas into protein LMs enables the development of next-generation interpretable machine-learning models with the potential of uncovering the biological mechanisms underlying sequence-function relationships.Comment: 27 pages, 4 figure

Going Digital: Creating Change in the Humanities: ALLEA E-HUMANITIES WORKING GROUP REPORT

The report is the output of the ALLEA Working Group on E-Humanities, chaired by Dr Sandra Collins, Director of the Digital Repository of Ireland at the Royal Irish Academy. Edited by Dr. Natalie Harrower, the report was co-written by experts in the Digital Humanities from six Academies across Europe. The report discusses the state of the art of Digital Humanities research and support structures in Europe, and makes key recommendations for the innovations required to foster the continued growth and excellence of the digital humanities in Europe, focusing on digital archiving, long-term preservation, digital research tools, sustained e-infrastructures and research networks. Structured around the data life-cycle, the report is aimed at a range of stakeholders, from humanities researchers to those working with data, and from university administrators to HSS and ICT funding bodies.Key recommendations include:Take a long-term view Sustaining long-term archives of unique and important cultural artefacts is critical for Europe’s leadership in Digital Humanities. Adopting best practice for infrastructures is essential.Encourage openness Open Access to data and infrastructures enables enhanced research, research integrity and cost-effectiveness. Open Data needs to be adequately funded.Support your people Training and career progression are essential to prevent the loss of the critical skills needed to retain our competitiveness in Europe. Data management roles need suitable recognition.ALLEA, the federation of All European Academies, was founded in 1994 and currently brings together 58 Academies in more than 40 countries from the Council of Europe region. Member Academies operate as learned societies, think tanks and research performing organisations. They are self- governing communities of leaders of scholarly enquiry across all fields of the natural sciences, the social sciences and the humanities. ALLEA therefore provides access to an unparalleled human resource of intellectual excellence, experience and expertise