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Abstract Background Recent studies suggest that low-molecular-weight heparin (LMWH) may play a role in mitigating the severity of acute pancreatitis (AP). This systematic review and meta-analysis aims to synthesise existing evidence on the effectiveness and safety of LMWH in the treatment of moderately-severe and severe AP. Methods This systematic review and meta-analysis was conducted in accordance with the 2020 update of the PRISMA guidelines and the Cochrane Handbook for Systematic Reviews of Interventions. The systematic search was conducted in MEDLINE, the Cochrane Central Register of Controlled Trials, Scopus, and EMBASE, covering studies published up to February 2024. Randomised controlled trials (RCTs) and observational studies (n-RCTs) that reported the differences in the outcomes of AP for patients receiving LMWH in addition to the standard treatment (Intervention), compared to patients managed by standard treatment without LMWH (Control) were eligible. A random-effects model was used to calculate the pooled relative risk (RR) and mean differences (MD) with the corresponding 95% CI. Results Thirteen studies were included in the meta-analysis, all published between 2004 and 2022. Eight studies were RCTs, and five were n-RCTs. Data from 13,709 patients (6.971 Interventions and 6.738 Controls) were analysed. The comparison of Intervention and Control groups showed the superiority of LMWH to standard treatments in terms of overall mortality (RR = 0.44, 95% CI = 0.31; 0.64, P

Partaking in the editorial process of an academic journal is both a challenging and rewarding experience. It takes a village of dedicated individuals with a vested interest in the dissemination and sharing of high-quality research outputs. As members of the editorial team of an open access data journal, we reflect on the emergence of data-driven open research, a new journal genre (data paper), and a new journal type (data journal) in the Arts, Humanities, and Social Sciences (AHSS). Access to data—the currency of empirical research—is valuable to the research community, crucial to scientific integrity, and leads to cumulative advancements in knowledge. It therefore requires significant investment and appropriate venues for dissemination. We illustrate the necessity of raising awareness about data-driven open research and best practices in data-driven publishing. We discuss how it involves building a community of authors and readers, establishing a company of editors, reviewers, and support staff, and passing on the practice, which has been challenging the status quo in research and publishing. Potential future directions are considered, including data peer review and reward, recognition, and funding structures for data sharing.

We present a series of workflows that aim to support research in lexical semantic change, i.e. the phenomenon by which words change their meaning over time. The workflows each consist of a series of steps required to detect words that have undergone semantic change as evidenced by a corpus and cover a range of user scenarios, including lexicology, historical research, and legal studies. The workflows were created following the model adopted by the Social Sciences and Humanities Open MarketPlace and were designed in the context of a project on CLARIN resource families supported by CLARIN ERIC. In this paper, we present a use case for the workflow on lexicology, referring to resources for Latin and ancient Greek.

In this paper, we present the diachronic maps of a selection of 75 Latin modal markers designed through the tool 'Pygmalion'. Both the maps and 'Pygmalion' were conceived in the framework of the 'WoPoss' project, which aims at analysing the diachronic pathways of modality in Latin. While the description of the tool and its functionalities is beyond the scope of this paper, we focus here on the description of our diachronic modal maps. Using visualisations to represent semantic shifts is a well-known practice in some linguistic fields such as typology and lexicography, and they have already been applied to modality. Though the situation is rapidly evolving, typological semantic maps as well as lexicographic maps are still for the most part static and usually not-interactive visualisations. Our modal maps stand out not only for their interactivity, but also for the richness of the information conveyed: chronology, etymology, semantics, syntax, first attestation and diachronic relationships between the meanings. After presenting our conceptual framework for modality, we illustrate the process of conceptualisation and development of our diachronic maps of modality. More specifically, we explain how we gathered and organised the data in order to transpose it into a visual representation. We then showcase the map of 'possum' as an example of our results. Subsequently, we discuss the results with respect to previous literature concerning both visualisation of modal evolution from a general point of view and the investigation of modality in Latin. Finally, we outline possible applications within and beyond the 'WoPoss' project.

The humanities and social sciences (HSS) have recently witnessed an exponential growth in data-driven research. In response, attention has been afforded to datasets and accompanying data papers as outputs of the research and dissemination ecosystem. In 2015, two data journals dedicated to HSS disciplines appeared in this landscape: Journal of Open Humanities Data (JOHD) and Research Data Journal for the Humanities and Social Sciences (RDJ). In this paper, we analyse the state of the art in the landscape of data journals in HSS using JOHD and RDJ as exemplars by measuring performance and the deep impact of data-driven projects, including metrics (citation count; Altmetrics, views, downloads, tweets) of data papers in relation to associated research papers and the reuse of associated datasets. Our findings indicate: that data papers are published following the deposit of datasets in a repository and usually following research articles; that data papers have a positive impact on both the metrics of research papers associated with them and on data reuse; and that Twitter hashtags targeted at specific research campaigns can lead to increases in data papers’ views and downloads. HSS data papers improve the visibility of datasets they describe, support accompanying research articles, and add to transparency and the open research agenda.