title: Duration of antibiotic therapy in critically ill patients: a randomized controlled trial of a clinical and C-reactive protein-based protocol versus an evidence-based best practice strategy without biomarkers

text: BACKGROUND: The rational use of antibiotics is one of the main strategies to limit the development of bacterial resistance. We therefore sought to evaluate the effectiveness of a C-reactive protein-based protocol in reducing antibiotic treatment time in critically ill patients. METHODS: A randomized, open-label, controlled clinical trial conducted in two intensive care units of a university hospital in Brazil. Critically ill infected adult patients were randomly allocated to (i) intervention to receive antibiotics guided by daily monitoring of CRP levels and (ii) control to receive antibiotics according to the best practices for rational use of antibiotics. RESULTS: One hundred thirty patients were included in the CRP (n = 64) and control (n = 66) groups. In the intention-to-treat analysis, the median duration of antibiotic therapy for the index infectious episode was 7.0 (5.0–8.8) days in the CRP and 7.0 (7.0–11.3) days in the control (p = 0.011) groups. A significant difference in the treatment time between the two groups was identified in the curve of cumulative suspension of antibiotics, with less exposure in the CRP group only for the index infection episode (p = 0.007). In the per protocol analysis, involving 59 patients in each group, the median duration of antibiotic treatment was 6.0 (5.0–8.0) days for the CRP and 7.0 (7.0–10.0) days for the control (p = 0.011) groups. There was no between-group difference regarding the total days of antibiotic exposure and antibiotic-free days. CONCLUSIONS: Daily monitoring of CRP levels may allow early interruption of antibiotic therapy in a higher proportion of patients, without an effect on total antibiotic consumption. The clinical and microbiological relevance of this finding remains to be demonstrated. TRIAL REGISTRY: ClinicalTrials.gov Identifier: NCT02987790. Registered 09 December 2016.


title: Emerging high-risk ST101 and ST307 carbapenem-resistant Klebsiella pneumoniae clones from bloodstream infections in Southern Italy

text: BACKGROUND: Carbapenem-resistant Klebsiella pneumoniae (CR-KP) is an urgent public health issue in Italy. This pattern of resistance is due mainly to dissemination of carbapenemase genes. Molecular characterization of carbapenem-resistant Klebsiella pneumoniae (CR-KP) strains was performed over a three-year period. In-depth analysis was performed on a subset of emerging CR-KP ST101 and ST307 clones. METHODS: A prospective study was performed on 691 patients with CR-KP bloodstream infections hospitalized in 19 hospitals located in three large provinces in Southern Italy. Carbapenemase genes were identified via genotyping methods. Multi-locus sequence typing (MLST) and Whole Genome Sequencing (WGS) were carried out on ST101 and ST307 isolates. RESULTS: Among the CR-KP isolates, bla(KPC) was found in 95.6%, bla(VIM) was found in 3.5%, bla(NDM) was found in 0.1% and bla(OXA-48) was found in 0.1%. The bla(KPC-3) variant was identified in all 104 characterized KPC-KP isolates. MLST of 231 representative isolates revealed ST512 in 45.5%, ST101 in 20.3% and ST307 in 18.2% of the isolates. cgMLST of ST307 and ST101 isolates revealed presence of more than one beta-lactam resistance gene. Amino acid substitution in the chromosomal colistin-resistance gene pmrB was found in two ST101 isolates. CONCLUSIONS: ST512 is widespread in Southern Italy, but ST101 and ST307 are emerging since they were found in a significant proportion of cases. Aggressive infection control measures and a continuous monitoring of these high-risk clones are necessary to avoid rapid spread of CR-KP, especially in hospital settings.


title: The gut microbiome’s role in the development, maintenance, and outcomes of sepsis

text: The gut microbiome regulates a number of homeostatic mechanisms in the healthy host including immune function and gut barrier protection. Loss of normal gut microbial structure and function has been associated with diseases as diverse as Clostridioides difficile infection, asthma, and epilepsy. Recent evidence has also demonstrated a link between the gut microbiome and sepsis. In this review, we focus on three key areas of the interaction between the gut microbiome and sepsis. First, prior to sepsis onset, gut microbiome alteration increases sepsis susceptibility through several mechanisms, including (a) allowing for expansion of pathogenic intestinal bacteria, (b) priming the immune system for a robust pro-inflammatory response, and (c) decreasing production of beneficial microbial products such as short-chain fatty acids. Second, once sepsis is established, gut microbiome disruption worsens and increases susceptibility to end-organ dysfunction. Third, there is limited evidence that microbiome-based therapeutics, including probiotics and selective digestive decontamination, may decrease sepsis risk and improve sepsis outcomes in select patient populations, but concerns about safety have limited uptake. Case reports of a different microbiome-based therapy, fecal microbiota transplantation, have shown correlation with gut microbial structure restoration and decreased inflammatory response, but these results require further validation. While much of the evidence linking the gut microbiome and sepsis has been established in pre-clinical studies, clinical evidence is lacking in many areas. To address this, we outline a potential research agenda for further investigating the interaction between the gut microbiome and sepsis.


title: Individual Heterogeneity in the Association Between Social Participation and Self-rated Health: A Panel Study on BHPS

text: In the last ten years, interest in social capital as a mechanism for understanding actual and perceived health has been increasing among economists. Although the pathways by which social participation, as a dimension of social capital, may have a positive effect on health seem clearly identified, empirical evidence is mixed because the lack of longitudinal data makes it difficult to deal with individual heterogeneity. Our study investigates the relationship between social participation (as measured by being a member, active, or both a member and active) in associations and self-rated health in a panel setting, using the first five waves of the British Household Panel Survey from 1991 to 1995 (unbalanced panel N = 45,745). To take into account heterogeneity, we implement three different kinds of estimations for fixed effects, two have been largely used in the literature and one method was recently proposed by Baetschmann et al. (J R Stat Soc Ser A 178: 685–703, 2015). We find positive effects but weak significance for active membership. When we control for reverse causality, using lagged independent variables and membership in specific organizations, we obtain more detailed and in some cases significant results.


title: Effect of a new respiratory care bundle on bronchopulmonary dysplasia in preterm neonates

text: The development of devices that can fix the tidal volume in high-frequency oscillatory ventilation (HFOV) has allowed for a significant improvement in the management of HFOV. At our institution, this had led to the earlier use of HFOV and promoted a change in the treatment strategy involving the use of higher frequencies (above 15 Hz) and lower high-frequency tidal volumes (VThf). The purpose of this observational study was to assess how survival without bronchopulmonary dysplasia grades 2 and 3 (SF-BPD) is influenced by these modifications in the respiratory strategy applied to preterm infants (gestational age < 32 weeks at birth) who required mechanical ventilation (MV) in the first 3 days of life. We compared a baseline period (2012–2013) against a period in which this strategy had been fully implemented (2016–2017). A total of 182 patients were exposed to MV in the first 3 days of life being a higher proportion on HFOV at day 3 in the second period 79.5% (n 35) in 2016–2017 vs 55.4% (n 31) in 2012–2013. After adjusting for perinatal risk factors, the second period is associated with an increased rate of SF-BPD (OR 2.28; CI 95% 1.072–4.878); this effect is more evident in neonates born at a gestational age of less than 29 weeks (OR 4.87; 95% CI 1.9–12.48). Conclusions : The early use of HFOV combined with the use of higher frequencies and very low VT was associated with an increase in the study population’s SF-BPD.


title: US–China Rivalry in the twenty-first century: Déjà vu and Cold War II

text: In 2019, US–China relations that had been characterized by a pattern of ups and downs over the past quarter century took a clear and possibly irreversible turn for the worse. This change has provoked debate about whether China and the US have already become rivals, perhaps adversaries, in a new cold war. I examine five underlying influences shaping the newly intensifying rivalry. These influences reflect key features of the international context within which the US and China find themselves (systemic or structural constraints) and the fact that the two rivals happen to be the US and China (national or unit-level attributes). Chief among the international constraints are the structural conditions of anarchy and the distribution of power that defines the system’s polarity. The national attributes most relevant to understanding the evolution of US–China relations are the geography of the theater where the two countries’ vital interests intersect and two aspects of their militarily relevant technological capabilities. Examining these five influences draws attention to reasons for some important similarities but also differences between the current rivalry and the Soviet–American rivalry of the Cold War. It makes clear that a Cold War II, if that is what is emerging, will not simply replicate the rivalry of Cold War I. Unfortunately, this examination also directs attention to some troubling new concerns about the distinctiveness of the new rivalry and the challenges they may present in the coming decades.


title: Salutogenic model of health to identify turning points and coping styles for eating practices in type 2 diabetes mellitus

text: BACKGROUND: It is important for people with Type 2 Diabetes Mellitus (T2DM) to eat healthily. However, implementing dietary advice in everyday life is difficult, because eating is not a distinguishable action, but a chain of activities, embedded in social practices and influenced by previous life experiences. This research aims to understand why and how eating practices are developed over the life-course by investigating influential life experiences – turning points – and coping strategies for eating practices of people with T2DM. METHODS: The Salutogenic Model of Health guided the study’s objective, study design and analysis. Seventeen interviews were performed and analysed based on the principles of interpretative phenomenological analysis. Narrative inquiry and the creation of timelines and food boxes were used as tools to facilitate reflection on turning points and eating practices. RESULTS: Turning points for unhealthier eating were experiences that strongly disturbed the participants’ emotional stability. These experiences included psychosocial trauma, physical health disorders, job loss, and smoking cessation. Turning points for healthier eating were experiences that significantly changed participants views on life and made participants reflective about the effects of current eating practices on future health and life goals. These turning points included confrontation with ill-health, becoming a parent, psychosocial therapy, and getting married. Notably, turning points for healthier eating seemed only to happen when life was relatively stress-free. All participants experienced turning points for healthier eating, yet, not all participants succeeded in improving their diets. Two coping styles were distinguished: active and passive coping. Active coping individuals were able to act in line with their personal intentions, whereas passive coping individuals could not. Differences between active and passive coping styles seemed to be explained by differences in available resources important for adapting and maintaining a healthy diet. CONCLUSION: Disadvantaged childhood and later life adversities together with the inability to manage the mental stress explained the development unhealthier eating practices. All participants experienced turning points for healthier eating that caused eating to become a priority in their life. Yet, the fact that not all were able to eat as they intended, advocates for nutritional guidance for people with T2DM, with a greater emphasis on reflexivity, psycho-social well-being and social support.


title: A Variability-Driven Analysis Method for Automatic Extraction of Domain Behaviors

text: Domain engineering focuses on modeling knowledge in an application domain for supporting systematic reuse in the context of complex and constantly evolving systems. Automatically supporting this task is challenging; most existing methods assume high similarity of variants which limits reuse of the generated domain artifacts, or provide very low-level features rather than actual domain features. As a result, these methods are limited in handling common scenarios such as similarly behaving systems developed by different teams, or merging existing products. To address this gap, we propose a method for extracting domain knowledge in the form of domain behaviors, building on a previously developed framework for behavior-based variability analysis among class operations. Machine learning techniques are applied for identifying clusters of operations that can potentially form domain behaviors. The approach is evaluated on a set of open-source video games, named apo-games.


title: Aspect Term Extraction Using Deep Learning Model with Minimal Feature Engineering

text: With the explosive growth of social media on the Web, opinion mining has been extensively investigated and consists of the automatic identification and extraction of opinions, emotions, and sentiments from text and multimedia data. One of the tasks involved in opinion mining is Aspect Term Extraction (ATE) which aims at identifying aspects (attributes or characteristics) that have been explicitly evaluated in a sentence or a document. For example, in the sentence “The picture quality of this camera is amazing”, the aspect term is “picture quality”. This work proposes POS-AttWD-BLSTM-CRF, a neural network architecture using a deep learning model, and minimal feature engineering, to solve the problem of ATE in opinionated documents. The proposed architecture consists of a BLSTM-CRF classifier that uses the part-of-speech tag (POS tags) as an additional feature, along with a BLSTM encoder with an attention mechanism to allow the incorporation of another relevant feature: the grammatical relations between words. The experiments show that the proposed architecture achieves promising results with minimal feature engineering comparing to the state-of-the-art solutions.


title: Query-Based Metrics for Evaluating and Comparing Document Schemas

text: Document stores are frequently used as representation format in many applications. It is often necessary to transform a set of data stored in a relational database (RDB) into a document store. There are several approaches that execute such translation. However, it is difficult to evaluate which target document structure is the most appropriate. In this article, we present a set of query-based metrics for evaluating and comparing documents schemas against a set of existing queries, that represent the application access pattern. We represent the target document schema and the queries as DAGs (Directed Acyclic Graphs), which are used to calculate the metrics. The metrics allow to evaluate if a given target document schema is adequate to answer the queries. We performed a set of experiments to calculate the metrics over a set of documents produced by existing transformation solutions. The metric results are related with smaller coding effort, showing that the metrics are effective to guide the choice of a target NoSQL document structure.


title: Co-destruction Patterns in Crowdsourcing: Formal/Technical Paper

text: Crowdsourcing has been a successful paradigm in organising a large number of actors to work on specific tasks and contribute to knowledge collectively. However, the openness of such systems allows destructive patterns to form through actors’ dynamics. As a result, the collective effort of actors may not achieve the targeted objective due to lower engagement and lower quality contributions. There are varying forms of actor dynamics that can lead to suboptimal outcomes and this paper provides a systematic analysis of these in the form of a collection of patterns, derived from both the literature and from our own experiences with crowdsourcing systems. This collection of so-called co-destruction patterns allows for an-depth analysis of corwdsourcing systems which can benefit a comparative analysis and also assist with improvements of existing systems or the set-up of new ones. A survey reveals that these patterns have been observed in practice and are perceived as worthwhile addressing.


title: Epilogue

text: It is mid-March 2020, and it is literally just a couple of days before the book goes into production. Universities, schools and play areas have been closed down all over Europe, and like so many other parents, we too are home schooling and having to find ways of occupying and entertaining our son ourselves. Not all products can be found in the shops and supermarkets, especially those needed for hygienic purposes such as toilet paper and soap. Washing one’s hands is named as the most important strategy for protection against the Corona virus.


title: Quantifying the Re-identification Risk of Event Logs for Process Mining: Empiricial Evaluation Paper

text: Event logs recorded during the execution of business processes constitute a valuable source of information. Applying process mining techniques to them, event logs may reveal the actual process execution and enable reasoning on quantitative or qualitative process properties. However, event logs often contain sensitive information that could be related to individual process stakeholders through background information and cross-correlation. We therefore argue that, when publishing event logs, the risk of such re-identification attacks must be considered. In this paper, we show how to quantify the re-identification risk with measures for the individual uniqueness in event logs. We also report on a large-scale study that explored the individual uniqueness in a collection of publicly available event logs. Our results suggest that potentially up to all of the cases in an event log may be re-identified, which highlights the importance of privacy-preserving techniques in process mining.


title: State Machine Based Human-Bot Conversation Model and Services

text: Task-oriented virtual assistants (or simply chatbots) are in very high demand these days. They employ third-party APIs to serve end-users via natural language interactions. Chatbots are famed for their easy-to-use interface and gentle learning curve (it only requires one of humans’ most innate ability, the use of natural language). Studies on human conversation patterns show, however, that day-to-day dialogues are of multi-turn and multi-intent nature, which pushes the need for chatbots that are more resilient and flexible to this style of conversations. In this paper, we propose the idea of leveraging Conversational State Machine to make it a core part of chatbots’ conversation engine by formulating conversations as a sequence of states. Here, each state covers an intent and contains a nested state machine to help manage tasks associated to the conversation intent. Such enhanced conversation engine, together with a novel technique to spot implicit information from dialogues (by exploiting Dialog Acts), allows chatbots to manage tangled conversation situations where most existing chatbot technologies fail.


title: Modeling and Analyzing Architectural Diversity of Open Platforms

text: Nowadays, successful software companies attain enhanced business objectives by opening their platforms to thousands of third-party providers. When developing an open platform many architectural design decisions have to be made, which are driven from the companies’ business objectives. The set of decisions results in an overwhelming design space of architectural variabilities. Until now, there are no architectural guidelines and tools that explicitly capture design variabilities of open platforms and their relation to business objectives. As a result, systematic knowledge is missing; platform providers have to fall back to ad-hoc decision-making; this bears consequences such as risks of failure and extra costs. In this paper, we present a pattern-driven approach called SecoArc to model diverse design decisions of open platforms and to analyze and compare alternative architectures with respect to business objectives. SecoArc consists of a design process, a modeling language, and an automated architectural analysis technique. It is implemented and ready-to-use in a tool. We evaluate the approach by means of a real-world case study. Results show that the approach improves the decision-making. Future platform providers can reduce risks by making informed decisions at design time.


title: Patterns for Certification Standards

text: One of the absolute preconditions for a safety-critical system to enter the market is to be issued a certificate by the regulating authorities. To this end, the “applicant” must demonstrate the compliance of its product with the domain’s standards. The high complexity of this process has led applicants to rely on assurance cases made for certification in the medical, nuclear, or aeronautic domains. In this paper, we propose a generic method that guides the applicant through the specification of assurance cases for a complex standard. Unlike existing works focused on a single context, our objective is to provide an approach that is both generic and domain-agnostic. In order to illustrate this new approach, we present the results of its application on a real-world case study, which pointed out new issues and led to improvements.


title: Workforce Upskilling: A History-Based Approach for Recommending Unfamiliar Process Activities

text: Human resource allocation decisions have a direct impact on the performance of a business process. Many approaches to optimal resource allocation have been proposed in the Business Process Management community. The majority of these approaches aim to optimise process performance; hence, recommend activities to experienced employees. To remain competitive, modern organisations also need to grow the capabilities of their employees and offer them upskilling opportunities. In this article, we propose an approach for recommending unfamiliar activities to employees by comparing their work histories with work histories of other similar employees. The aim of the proposed approach is to put employees on a gradual path of multi-skilling whereby they are provided with an opportunity to perform unfamiliar process activities and thus gain their experience through learning-by-doing. The approach is based on the analysis of process execution data and has been implemented. In the evaluation, we compared recommendations provided by the approach with actual activity executions of different employees recorded in process data. The evaluation demonstrated the effectiveness of the approach for different publicly available event logs and configuration settings.


title: Evaluating the Benefits of Model-Driven Development: Empirical Evaluation Paper

text: Researchers have been evaluating the benefits of Model-Driven Development (MDD) for more than a decade now. Although some works suggest that MDD decreases development time, other works limit MDD benefits to academic exercises and to developers without experience. To clarify the benefits of MDD, we present the results of our experiment, which compares MDD and Code-centric Development (CcD) in terms of correctness, efficiency, and satisfaction. Our experiment achieves fidelity to real-world settings because the tasks are taken from real-world video game development, and the subjects use domain frameworks as they are used in real-world developments. Our results challenge previous ideas that limit the benefits of MDD to academic exercises and to developers without experience. Furthermore, our results also suggest that understanding the benefits of MDD might require researchers to rethink their experiments to include the social part of software development.


title: Data Sovereignty and the Internet of Production

text: While the privacy of personal data has captured great attention in the public debate, resulting, e.g., in the European GDPR guideline, the sovereignty of knowledge-intensive small and medium enterprises concerning the usage of their own data in the presence of dominant data-hungry players in the Internet needs more investigation. In Europe, even the legal concept of data ownership is unclear. We reflect on requirements analyses, reference architectures and solution concepts pursued by the International Data Spaces Initiative to address these issues. The second part will more deeply explore our current interdisciplinary research in a visionary “Internet of Production” with 27 research groups from production and materials engineering, computer science, business and social sciences. In this setting, massive amounts of heterogeneous data must be exchanged and analyzed across organizational and disciplinary boundaries, throughout the lifecycle from (re-)engineering, to production, usage and recycling, under hard resource and time constraints. A shared metaphor, borrowed from Plato’s famous Cave Allegory, serves as the core modeling and data management approach from conceptual, logical, physical, and business perspectives.


title: A Combined Method for Usage of NLP Libraries Towards Analyzing Software Documents

text: Natural Language Processing (NLP) library is widely used while analyzing software documents. The numerous toolkits result in a problem on NLP library selection. The selection of NLP library in current work commonly misses some objective reasons, which may pose threats to validity. And it is also not clear that whether the existing guideline on selection still works for the latest versions. In this work, we propose a solution for NLP library selection when the effectiveness is unknown. We use the NLP libraries together in a combined method. Our combined method can utilize the strengths of different NLP libraries to obtain accurate results. The combination is conducted through two steps, i.e., document-level selection of NLP library and sentence-level overwriting. In document-level selection of primary library, the results are obtained from the library that has the highest overall accuracy. Through sentence-level overwriting, the possible fine-gained improvements from other libraries are extracted to overwrite the outputs of primary library. We evaluate the combined method with 4 widely used NLP libraries and 200 documents from 3 different sources. The results show that the combined method can generally outperform all the studied NLP libraries in terms of accuracy. The finding means that our combined method can be used instead of individual NLP library for more effective results.


title: Resource-Based Adaptive Robotic Process Automation: Formal/Technical Paper

text: Robotic process automation is evolving from robots mimicking human workers in automating information acquisition tasks, to robots performing human decision tasks using machine learning algorithms. In either of these situations, robots or automation agents can have distinct characteristics in their performance, much like human agents. Hence, the execution of an automated task may require adaptations with human participants executing the task when robots fail, to taking a supervisory role or having no involvement. In this paper, we consider different levels of automation, and the corresponding coordination required by resources that include human participants and robots. We capture resource characteristics and define business process constraints that support process adaptations with human-automation coordination. We then use a real-world business process and incorporate automation agents, compute resource characteristics, and use resource-aware constraints to illustrate resource-based process adaptations for its automation.


title: A System Framework for Personalized and Transparent Data-Driven Decisions

text: Decision support systems that rely on data analytics are used in numerous applications. Their advantages are indisputable, however, they also present risks, possibly having severe impact on people’s lives. Consequently, the need to support ethical or responsible behavior of such systems has recently emerged, putting an emphasis on ensuring fairness, transparency, accountability, etc. This paper presents a novel system framework that offers transparent and personalized services tailored to user profiles to serve their best interest. Our framework personalizes the choice of model for individuals or groups of users based on metadata about data sets and machine learning models. Querying and processing these metadata ensures transparency by supporting various kinds of queries by different stakeholders. We discuss our framework in detail, show why existing solutions are inadequate, and highlight research questions that need to be tackled in the future. Based on a prototypical implementation, we showcase that even a baseline implementation of our framework supports the desired transparency and personalization.


title: Recommendations for Evolving Relational Databases

text: Relational databases play a central role in many information systems. Their schemas contain structural and behavioral entity descriptions. Databases must continuously be adapted to new requirements of a world in constant change while: (1) relational database management systems (RDBMS) do not allow inconsistencies in the schema; (2) stored procedure bodies are not meta-described in RDBMS such as PostgreSQL that consider their bodies as plain text. As a consequence, evaluating the impact of an evolution of the database schema is cumbersome, being essentially manual. We present a semi-automatic approach based on recommendations that can be compiled into a SQL patch fulfilling RDBMS constraints. To support recommendations, we designed a meta-model for relational databases easing computation of change impact. We performed an experiment to validate the approach by reproducing a real evolution on a database. The results of our experiment show that our approach can set the database in the same state as the one produced by the manual evolution in 75% less time.


title: Workarounds in Business Processes: A Goal-Based Analysis

text: Workarounds in business processes and information systems (IS) have attracted research attention in recent years. Deviating from official processes, workarounds are goal-driven adaptations. Understanding the underlying problems or perceived barriers that motivate workarounds is essential for suggesting appropriate solutions which would lead to process and IS improvement. The premise taken in this paper is that workarounds are often motivated by misalignments between organizational goals, goals of local-units and actors, and the business process that should realize these goals. With this premise, we propose an i*-based analysis for identifying such misalignments that are associated to workarounds. We report an industrial case study that demonstrates the analysis and associates workarounds with the underlying misalignments. Improvement recommendations that were made following the analysis have been accepted by the organization and are currently being implemented.


title: B-MERODE: A Model-Driven Engineering and Artifact-Centric Approach to Generate Blockchain-Based Information Systems

text: Blockchain technology has the potential to facilitate the development and improvement of cross-organizational business processes. When it comes to developing systems relying on blockchain having this purpose, model-driven engineering is a promising approach that has been adopted by a number of solutions. This paper presents B-MERODE, a novel approach relying on model-driven engineering and artifact-centric business processes to generate blockchain-based information systems supporting cross-organizational collaborations. The feasibility of the approach is demonstrated by modeling the case of a rice supply chain. Compared to other solutions, B-MERODE provides more flexibility, more reusability and further leverages the automation potential offered by model-driven engineering.


title: LoGo: Combining Local and Global Techniques for Predictive Business Process Monitoring

text: Predicting process behavior in terms of the next activity to be executed and/or its timestamp can be crucial, e.g., to avoid impeding compliance violations or performance problems. Basically, two prediction techniques are conceivable, i.e., global and local techniques. Global techniques consider all process behavior at once, but might suffer from noise. Local techniques consider a certain subset of the behavior, but might loose the “big picture”. A combination of both techniques is promising to balance out each others drawbacks, but exists so far only in an implicit and unsystematic way. We propose LoGo as a systematic combined approach based on a novel global technique and an extended local one. LoGo is evaluated based on real life execution logs from multiple domains, outperforming nine comparison approaches. Overall, LoGo results in explainable prediction models and high prediction quality.


title: Information Systems Engineering with Digital Shadows: Concept and Case Studies: An Exploratory Paper

text: The production sector has faced many difficulties in taking full advantage of opportunities found in other web application domains. Production research has focused on sophisticated mathematical models ranging from molecular materials modeling to efficient production control to inter-company supply network logistics. Often, these models have no closed-form solutions; this led to intense simulation research for individual modeling viewpoints, often labeled “Digital Twins”. However, the complexity of the overall system precludes Digital Twins covering more than just a few system perspectives, especially if near-realtime performance is required. Moreover, the wide variety of individual situations and behaviors is usually captured only as statistical uncertainty. In order to achieve better performance and more context adaptation, the interdisciplinary research cluster “Internet of Production” at RWTH Aachen University is exploring the concept of “Digital Shadows”. Digital Shadows can be understood as compact views on dynamic processes, usually combining condensed measurement data with highly efficient simplified mathematical models. In this exploratory paper, we argue based on a couple of initial case studies that Digital Shadows are not just valuable carriers of deep engineering knowledge but due to their small size also help in reducing network congestion and enabling edge computing. These properties could make Digital Shadows an interesting solution to address resilience in other information-intensive dynamic systems.


title: Information Extraction and Graph Representation for the Design of Formulated Products

text: Formulated products like cosmetics, personal and household care, and pharmaceutical products are ubiquitous in everyday life. The multi-billion-dollar formulated products industry depends primarily on experiential knowledge for the design of new products. Vast knowledge of formulation ingredients and recipes exists in offline and online resources. Experts often use rudimentary searches over this data to find ingredients and construct recipes. This state of the art leads to considerable time to market and cost. We present an approach for formulated product design that enables extraction, storage, and non-trivial search of details required for product variant generation. Our contributions are threefold. First, we show how various information extraction techniques can be used to extract ingredients and recipe actions from textual sources. Second, we describe how to store this highly connected information as a graph database with an extensible domain model. And third, we demonstrate an aid to experts in putting together a new product based on non-trivial search. In an ongoing proof of concept, we use 410 formulations of various cosmetic creams to demonstrate these capabilities with promising results.


title: Model-Driven Development of a Digital Twin for Injection Molding

text: Digital Twins (DTs) of Cyber-Physical Production Systems (CPPSs) enable the smart automation of production processes, collection of data, and can thus reduce manual efforts for supervising and controlling CPPSs. Realizing DTs is challenging and requires significant efforts for their conception and integration with the represented CPPS. To mitigate this, we present an approach to systematically engineering DTs for injection molding that supports domain-specific customizations and automation of essential development activities based on a model-driven reference architecture. In this approach, reactive CPPS behavior is defined in terms of a Domain-Specific Language (DSL) for specifying events that occur in the physical system. The reference architecture connects to the CPPS through a novel DSL for representing OPC-UA bindings. We have evaluated this approach with a DT of an injection molding machine that controls the machine to optimize the Design of Experiment (DoE) parameters between experiment cycles before the products are molded. Through this, our reference implementation of the DT facilitates the time-consuming setup of a DT and the subsequent injection molding activities. Overall, this facilitates to systematically engineer digital twins with reactive behavior that help to optimize machine use.


title: SIoTPredict: A Framework for Predicting Relationships in the Social Internet of Things

text: The Social Internet of Things (SIoT) is a new paradigm that integrates social network concepts with the Internet of Things (IoT). It boosts the discovery, selection and composition of services and information provided by distributed objects. In SIoT, searching for services is based on the utilization of the social structure resulted from the formed relationships. However, current approaches lack modelling and effective analysis of SIoT. In this work, we address this problem and specifically focus on modelling the SIoT’s evolvement. As the growing number of IoT objects with heterogeneous attributes join the social network, there is an urgent need for identifying the mechanisms by which SIoT structures evolve. We model the SIoT over time and address the suitability of traditional analytical procedures to predict future relationships (links) in the dynamic and heterogeneous SIoT. Specifically, we propose a framework, namely SIoTPredict, which includes three stages: i) collection of raw movement data of IoT devices, ii) generating temporal sequence networks of the SIoT, and iii) predicting relationships among IoT devices which are likely to occur. We have conducted extensive experimental studies to evaluate the proposed framework using real SIoT datasets and the results show the better performance of our framework.


title: Mining User Opinions to Support Requirement Engineering: An Empirical Study

text: App reviews provide a rich source of user opinions that can support requirement engineering activities. Analysing them manually to find these opinions, however, is challenging due to their large quantity and noisy nature. To overcome the problem, automated approaches have been proposed for so-called opinion mining. These approaches facilitate the analysis by extracting features discussed in app reviews and identifying their associated sentiments. The effectiveness of these approaches has been evaluated using different methods and datasets. Unfortunately, replicating these studies to confirm their results and to provide benchmarks of different approaches is a challenging problem. We address the problem by extending previous evaluations and performing a comparison of these approaches. In this paper, we present an empirical study in which, we evaluated feature extraction and sentiment analysis approaches on the same dataset. The results show these approaches achieve lower effectiveness than reported originally, and raise an important question about their practical use.


title: An Approach for Process Model Extraction by Multi-grained Text Classification

text: Process model extraction (PME) is a recently emerged interdiscipline between natural language processing (NLP) and business process management (BPM), which aims to extract process models from textual descriptions. Previous process extractors heavily depend on manual features and ignore the potential relations between clues of different text granularities. In this paper, we formalize the PME task into the multi-grained text classification problem, and propose a hierarchical neural network to effectively model and extract multi-grained information without manually-defined procedural features. Under this structure, we accordingly propose the coarse-to-fine (grained) learning mechanism, training multi-grained tasks in coarse-to-fine grained order to share the high-level knowledge for the low-level tasks. To evaluate our approach, we construct two multi-grained datasets from two different domains and conduct extensive experiments from different dimensions. The experimental results demonstrate that our approach outperforms the state-of-the-art methods with statistical significance and further investigations demonstrate its effectiveness.


title: DeepAlign: Alignment-Based Process Anomaly Correction Using Recurrent Neural Networks

text: In this paper, we propose DeepAlign, a novel approach to multi-perspective process anomaly correction, based on recurrent neural networks and bidirectional beam search. At the core of the DeepAlign algorithm are two recurrent neural networks trained to predict the next event. One is reading sequences of process executions from left to right, while the other is reading the sequences from right to left. By combining the predictive capabilities of both neural networks, we show that it is possible to calculate sequence alignments, which are used to detect and correct anomalies. DeepAlign utilizes the case-level and event-level attributes to closely model the decisions within a process. We evaluate the performance of our approach on an elaborate data corpus of 252 realistic synthetic event logs and compare it to three state-of-the-art conformance checking methods. DeepAlign produces better corrections than the rest of the field reaching an overall [Formula: see text] score of 0.9572 across all datasets, whereas the best comparable state-of-the-art method reaches 0.6411.


title: Mutation Operators for Large Scale Data Processing Programs in Spark

text: This paper proposes a mutation testing approach for big data processing programs that follow a data flow model, such as those implemented on top of Apache Spark. Mutation testing is a fault-based technique that relies on fault simulation by modifying programs, to create faulty versions called mutants. Mutant creation is carried on by operators able to simulate specific and well identified faults. A testing process must be able to signal faults within mutants and thereby avoid having ill behaviours within a program. We propose a set of mutation operators designed for Spark programs characterized by a data flow and data processing operations. These operators model changes in the data flow and operations, to simulate faults that take into account Spark program characteristics. We performed manual experiments to evaluate the proposed mutation operators in terms of cost and effectiveness. Thereby, we show that mutation operators can contribute to the testing process, in the construction of reliable Spark programs.


title: Decentralized Cross-organizational Application Deployment Automation: An Approach for Generating Deployment Choreographies Based on Declarative Deployment Models

text: Various technologies have been developed to automate the deployment of applications. Although most of them are not limited to a specific infrastructure and able to manage multi-cloud applications, they all require a central orchestrator that processes the deployment model and executes all necessary tasks to deploy and orchestrate the application components on the respective infrastructure. However, there are applications in which several organizations, such as different departments or even different companies, participate. Due to security concerns, organizations typically do not expose their internal APIs to the outside or leave control over application deployments to others. As a result, centralized deployment technologies are not suitable to deploy cross-organizational applications. In this paper, we present a concept for the decentralized cross-organizational application deployment automation. We introduce a global declarative deployment model that describes a composite cross-organizational application, which is split to local parts for each participant. Based on the split declarative deployment models, workflows are generated which form the deployment choreography and coordinate the local deployment and cross-organizational data exchange. To validate the practical feasibility, we prototypical implemented a standard-based end-to-end toolchain for the proposed method using TOSCA and BPEL.


title: Conformance Checking Approximation Using Subset Selection and Edit Distance

text: Conformance checking techniques let us find out to what degree a process model and real execution data correspond to each other. In recent years, alignments have proven extremely useful in calculating conformance statistics. Most techniques to compute alignments provide an exact solution. However, in many applications, it is enough to have an approximation of the conformance value. Specifically, for large event data, the computation time for alignments is considerably long using current techniques which makes them inapplicable in reality. Also, it is no longer feasible to use standard hardware for complex process models. This paper, proposes new approximation techniques to compute approximated conformance checking values close to exact solution values in less time. These methods also provide upper and lower bounds for the approximated alignment value. Our experiments on real event data show that it is possible to improve the performance of conformance checking by using the proposed methods compared to using the state-of-the-art alignment approximation technique. Results show that in most of the cases, we provide tight bounds, accurate approximated alignment values, and similar deviation statistics.


title: Business Process Variant Analysis Based on Mutual Fingerprints of Event Logs

text: Comparing business process variants using event logs is a common use case in process mining. Existing techniques for process variant analysis detect statistically-significant differences between variants at the level of individual entities (such as process activities) and their relationships (e.g. directly-follows relations between activities). This may lead to a proliferation of differences due to the low level of granularity in which such differences are captured. This paper presents a novel approach to detect statistically-significant differences between variants at the level of entire process traces (i.e. sequences of directly-follows relations). The cornerstone of this approach is a technique to learn a directly-follows graph called mutual fingerprint from the event logs of the two variants. A mutual fingerprint is a lossless encoding of a set of traces and their duration using discrete wavelet transformation. This structure facilitates the understanding of statistical differences along the control-flow and performance dimensions. The approach has been evaluated using real-life event logs against two baselines. The results show that at a trace level, the baselines cannot always reveal the differences discovered by our approach, or can detect spurious differences.


title: Stochastic-Aware Conformance Checking: An Entropy-Based Approach

text: Business process management (BPM) aims to support changes and innovations in organizations’ processes. Process mining complements BPM with methods, techniques, and tools that provide insights based on observed executions of business processes recorded in event logs of information systems. State-of-the-art discovery and conformance techniques completely ignore or only implicitly consider the information about the likelihood of processes, which is readily available in event logs, even though such stochastic information is necessary for simulation, prediction and recommendation in models. Furthermore, stochastic information can provide business analysts with further actionable insights on frequent and rare conformance issues. In this paper, we propose precision and recall conformance measures based on the notion of entropy of stochastic automata that are capable of quantifying, and thus differentiating, frequent and rare deviations between an event log and a process model. The feasibility of using the proposed precision and recall measures in industrial settings is demonstrated by an evaluation over several real-world datasets supported by our open-source implementation.


title: Smart Contract Invocation Protocol (SCIP): A Protocol for the Uniform Integration of Heterogeneous Blockchain Smart Contracts

text: Blockchains are distributed ledgers that enable the disintermediation of collaborative processes and, at the same time, foster trust among partners. Modern blockchains support smart contracts, i.e., software deployed on the blockchain, and guarantee their repeatable, deterministic execution. Alas, blockchains and smart contracts lack standardization. Therefore, smart contracts come with heterogeneous properties, APIs and data formats. This hinders the integration of smart contracts running in different blockchains, e.g., into enterprise business processes. This paper introduces the Smart Contract Invocation Protocol (SCIP), which unifies interacting with smart contracts of different blockchains. The protocol supports invoking smart contract functions, monitoring function executions, emitted events, and transaction finality, as well as querying a blockchain. The protocol is accompanied by a prototypical implementation of a SCIP endpoint in the form of a gateway.


title: Remodularization Analysis for Microservice Discovery Using Syntactic and Semantic Clustering

text: This paper addresses the challenge of automated remodularization of large systems as microservices. It focuses on the analysis of enterprise systems, which are widely used in corporate sectors and are notoriously large, monolithic and challenging to manually decouple because they manage asynchronous, user-driven business processes and business objects (BOs) having complex structural relationships. The technique presented leverages semantic knowledge of enterprise systems, i.e., BO structure, together with syntactic knowledge of the code, i.e., classes and interactions as part of static profiling and clustering. On a semantic level, BOs derived from databases form the basis for prospective clustering of classes as modules, while on a syntactic level, structural and interaction details of classes provide further insights for module dependencies and clustering, based on K-Means clustering and optimization. Our integrated techniques are validated using two open source enterprise customer relationship management systems, SugarCRM and ChurchCRM. The results demonstrate improved feasibility of remodularizing enterprise systems (inclusive of coded BOs and classes) as microservices. Furthermore, the recommended microservices, integrated with ‘backend’ enterprise systems, demonstrate improvements in key non-functional characteristics, namely high execution efficiency, scalability and availability.


title: Online Reinforcement Learning for Self-adaptive Information Systems

text: A self-adaptive information system is capable of maintaining its quality requirements in the presence of dynamic environment changes. To develop a self-adaptive information system, information system engineers have to create self-adaptation logic that encodes when and how the system should adapt itself. However, developing self-adaptation logic may be difficult due to design time uncertainty; e.g., anticipating all potential environment changes at design time is in most cases infeasible. Online reinforcement learning (RL) addresses design time uncertainty by learning the effectiveness of adaptation actions through interactions with the system’s environment at run time, thereby automating the development of self-adaptation logic. Existing online RL approaches for self-adaptive information systems exhibit two shortcomings that limit the degree of automation: they require manually fine-tuning the exploration rate and may require manually quantizing environment states to foster scalability. We introduce an approach to automate the aforementioned manual activities by employing policy-based RL as a fundamentally different type of RL. We demonstrate the feasibility and applicability of our approach using two self-adaptive information system exemplars.


title: Digging into Business Process Meta-models: A First Ontological Analysis

text: While modern definitions of business processes exist and are shared in the Business Process Management community, a commonly agreed meta-model is still missing. Nonetheless, several different business process meta-models have been recently proposed and discussed in the literature, which look at business process models from different perspectives, focusing on different aspects and often using different labels for denoting the same element or element relation. In this paper, we start from elements and relations discovered inspecting the literature on business process meta-models through a systematic literature review. We then combine these elements and relations to build a business process meta-model. The obtained literature-based business process meta-model, which is on purpose built to disclose criticalities, is then inspected and discussed. The analysis reveals, besides the lack of attention to some crucial business process elements, issues and inconsistencies in the literature meta-models. An ontological analysis is finally carried out and possible solutions to the discovered issues are proposed.


Cancer detection: the quest for a single liquid biopsy for all


Global outbreak research: harmony not hegemony


19th European Congress of Internal Medicine 18-20 March 2021


title: DMI fuel cell drone delivers face masks to remote Korean islands

text: Doosan Mobility Innovation has used its hydrogen PEM fuel cell drone to distribute protective face masks to residents on several small islands around Jeju Island, off the southwestern tip of South Korea.


COVID-19 and the US health insurance conundrum


Lessons What We Learned in Korea: Shield the Medical Facilities and Health Care Providers


title: New Media and Youth Political Engagement

text: This article critically examines the role new media can play in the political engagement of young people in Australia. Moving away from “deficit” descriptions, which assert low levels of political engagement among young people, it argues two major points. First, that there is a well-established model of contemporary political mobilisation that employs both new media and large data analysis that can and have been effectively applied to young people in electoral and non-electoral contexts. Second, that new media, and particularly social media, are not democratic by nature. Their general use and adoption by young and older people do not necessarily cultivate democratic values. This is primarily due to the type of participation afforded in the emerging “surveillance economy”. The article argues that a focus on scale as drivers of influence, the underlying foundation of their affordances based on algorithms, and the centralised editorial control of these platforms make them highly participative, but unequal sites for political socialisation and practice. Thus, recent examples of youth mobilisation, such as seen in recent climate justice movements, should be seen through the lens of cycles of contestation, rather than as technologically determined.


title: Up-regulation of miR-146b-3p protects septic mice with acute respiratory distress syndrome by inhibiting PI3K/AKT signaling pathway

text: This study aimed to explore the role of miR-146b-3p in acute respiratory distress syndrome in septic mice. Ten mice were randomly selected as normal group (n = 10, without any treatment) and 60 septic mice with acute respiratory distress syndrome were divided into model group (n = 10, without any treatment), negative control (NC) mimic group (n = 10, injected with NC mimic), miR-146b-3p mimic group (n = 10, injected with miR-146b-3p mimic), si-NC group (n = 10, injected with PI3Kγ siRNA NC), si-PI3Kγ group (n = 10, injected with PI3Kγ silencing plasmid), and miR-146b-3p mimic + oe-PI3Kγ group (n = 10, injected with miR-146b-3p mimic + PI3Kγ overexpression plasmid). We found that miR-146b-3p negatively regulated PI3Kγ. Compared with normal group, model mice had decreased expression of miR-146b-3p, increased expressions of PI3Kγ, p-AKT, ASC, NLRP3 and Caspase-1 proteins, higher W/D ratio, and more serum IL-1β and IL-18 content (all P < 0.05). All indicators in miR-146b-3p mimic group and si-PI3Kγ group were significantly improved as compared to model group (all P < 0.05). Over-expression of PI3Kγ could weaken the treatment effect of miR-146b-3p mimic in model mice. Therefore, up-regulation of miR-146b-3p can inhibit PI3K/AKT signaling pathway to improve acute respiratory distress syndrome in septic mice.


title: Is MOOC Learning Different for Dropouts? A Visually-Driven, Multi-granularity Explanatory ML Approach

text: Millions of people have enrolled and enrol (especially in the Covid-19 pandemic world) in MOOCs. However, the retention rate of learners is notoriously low. The majority of the research work on this issue focuses on predicting the dropout rate, but very few use explainable learning patterns as part of this analysis. However, visual representation of learning patterns could provide deeper insights into learners’ behaviour across different courses, whilst numerical analyses can – and arguably, should – be used to confirm the latter. Thus, this paper proposes and compares different granularity visualisations for learning patterns (based on clickstream data) for both course completers and non-completers. In the large-scale MOOCs we analysed, across various domains, our fine-grained, fish-eye visualisation approach showed that non-completers are more likely to jump forward in their learning sessions, often on a ‘catch-up’ path, whilst completers exhibit linear behaviour. For coarser, bird-eye granularity visualisation, we observed learners’ transition between types of learning activity, obtaining typed transition graphs. The results, backed up by statistical significance analysis and machine learning, provide insights for course instructors to maintain engagement of learners by adapting the course design to not just ‘dry’ predicted values, but explainable, visually viable paths extracted.


title: Multi-sensual Augmented Reality in Interactive Accessible Math Tutoring System for Flipped Classroom

text: Evermore widespread “flipped classroom” learning model is associated with increased independence of learning. The problem is the independence of learning math by students with visual impairments, especially the blind. Mathematical content includes spatial objects such as formulas and graphics, inaccessible to blind students and hardly accessible to low vision students. They prevent independent learning. The article presents a method that increases students’ independence in recognising mathematical content in textbooks and worksheets. The method consists in introducing into the document elements of Augmented Reality (AR), that is texts and sounds extending information about the mathematical objects encountered in the content, beyond the information provided by WCAG guidelines and recommendations of the WAI-ARIA standard under development by the W3C consortium. Access to AR elements is gained through multi-sensual User Interface - hearing, the touch of a braille display, touch screen and touch gestures. The method was developed in cooperation with students with visual impairment and math teachers. It is currently undergoing valorisation in Poland, the Netherlands and Ireland.


title: Caffeine for the Treatment of Apnea in the Neonatal Intensive Care Unit: A Systematic Overview of Meta-Analyses

text: BACKGROUND: Caffeine is a common treatment for neonatal intensive care management of the developmental complication of apnea of prematurity in preterm infants. There are several systematic reviews (SRs) on the performance of caffeine in the treatment of apnea. The evidence provided by those, however, is depressed by an information overload due to high heterogeneity in the characteristics as well as the quality of these SRs. OBJECTIVE: The aim was to provide a systematic overview of SRs on the use of caffeine for the management of neonatal apnea. Such overviews are a recent method used to assess and filter top evidence among SRs, enabling enhanced access to targeted information of interest. METHODS: A comprehensive literature search was conducted via EMBASE, Cochrane Database of Systematic Reviews (CDSR), and PubMed since inception to January 2020. Two reviewers independently conducted study selection and data extraction, and assessed the quality of methods and the risk of bias in included SRs based on A Measurement Tool to Assess Systematic Reviews (AMSTAR-2) and Risk of Bias in Systematic Reviews (ROBIS) tools. Extracted data related to study type, characteristics, patients, intervention, comparator, regimen, and outcome measures. RESULTS: Seven SRs with meta-analyses (SRMAs) were included in the current overview, involving a total of 63,315 neonates. SRMAs included randomized clinical and observational studies, with various types of patients, comparators, and outcomes. The quality of SRMAs ranged from critically low (n = 1), low (n = 1), moderate (n = 2), to high (n = 3), and the risk of bias was unclear (n = 2), low (n = 4), and high (n = 1). The effectiveness of caffeine with regard to treatment success and the rate of apnea was not significantly different from that of theophylline or doxapram in two SRMAs. Against control, in one SRMA, while caffeine reduced the rate of failure as well as the need for pressure ventilation, it did not significantly reduce mortality. This comparative effectiveness of caffeine was based on high-quality SRMAs with a low risk of bias. The effectiveness against apnea seems to be enhanced via the administration of early (0–2 days) or high doses of caffeine in one and three SRMAs, respectively. This, nevertheless, was based on lower-quality SRMAs with a higher risk of bias. Safety outcomes were mostly based on comparative SRMAs of different drug regimens, whereby, less tachycardia and lower risk for complications were reported with lower and earlier caffeine administrations, respectively. The evidence behind this, however, was limited in quantity and quality. CONCLUSION: While limited in quantity, there is evidence of non-inferior effectiveness of caffeine against other methylxanthines or doxapram for the management of apnea in neonates. Owing to the limited quality, however, limited evidence exists in support of an optimal administration regimen for caffeine. Further controlled studies are, therefore, needed to confirm the comparative usefulness of caffeine as well as to assess its different potential regimens, including in relation to safety. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s40272-020-00404-4) contains supplementary material, which is available to authorized users.


title: Suspending Medical Student Clerkships Due to COVID-19

text: Medical schools around the world have been grappling with how to adapt undergraduate medical curricula in the face of the COVID-19 pandemic. Our institution made the decision to suspend all clinical clerkships the day before the Association of American Medical Colleges (AAMC) recommended to US medical schools a similar suspension of “medical student participation in any activities that involved patient contact.” This manuscript describes the rapid evolution in our decision-making as we weighed various information, values, and priorities in the face of the emerging public health crisis. We discuss how a compromised learning environment and concerns about student, patient, and the public health led to the suspension. We also consider next steps as we move forward in this uncertain time.


title: Preparing for the next generation pharmacists

text: To address the changes in health care and the needs of society related to medicines, we must redefine the profession of pharmacy. We have defined the next generation pharmacists (NGP) as “a health care provider and change agent on the interprofessional health care team, personalizing medication use, managing safe and effective medication systems, and creating healthier communities.” Schools and colleges of pharmacy should thoroughly examine their curriculum to ensure it is preparing pharmacists for this future. By creating a vision for the NGP and implementing the best curriculum, we ensure that pharmacists of the future will be up to the challenge of our society’s health care needs..


title: Influenza-associated aspergillosis in critically-ill patients—a retrospective bicentric cohort study

text: Influenza was recently reported as a risk factor for invasive aspergillosis (IA). We aimed to describe prognostic factors for influenza-associated IA (IAA) and poor outcome and mortality in critically ill patients in Switzerland. All adults with confirmed influenza admitted to the ICU at two Swiss tertiary care centres during the 2017/2018 influenza season were retrospectively evaluated. IAA was defined by clinical, mycological and radiological criteria: a positive galactomannan in bronchoalveolar lavage or histopathological or cultural evidence in respiratory specimens of Aspergillus spp., any radiological infiltrate and a compatible clinical presentation. Poor outcome was defined as a composite of in-hospital mortality, ICU length of stay (LOS), invasive ventilation for > 7 days or extracorporeal membrane oxygenation. Of 81 patients with influenza in the ICU, 9 (11%) were diagnosed with IAA. All patients with IAA had poor outcome compared to 26 (36%) patients without IAA (p < 0.001). Median ICU-LOS and mortality were 17 vs. 3 days (p < 0.01) and 3/9 (33%) vs. 13/72 (18%; p = 0.37) in patients with vs. without IAA, respectively. Patients with IAA had significantly longer durations of antibiotic therapy, vasoactive support and mechanical ventilation. Aspergillus was the most common respiratory co-pathogen (9/40, 22%) followed by classical bacterial co-pathogens. IAA was not associated with classical risk factors. Aspergillus is a common superinfection in critically ill influenza patients associated with poor outcome and longer duration of organ supportive therapies. Given the absence of classical risk factors for aspergillosis, greater awareness is necessary, particularly in those requiring organ supportive therapies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10096-020-03923-7) contains supplementary material, which is available to authorized users.


title: Method for the elucidation of LAMP products captured on lateral flow strips in a point of care test for HPV 16

text: Loop-mediated amplification (LAMP) is an isothermal amplification technique favored in diagnostics and point-of-care work due to its high sensitivity and ability to run in isothermal conditions. In addition, a visual readout by lateral flow strips (LFS) can be used in conjunction with LAMP, making the assay accessible at the point-of-care. However, the amplicons resulting from a LAMP reaction varied in length and shape, making them undiscernible on a double-stranded DNA intercalating dye stained gel. Standard characterization techniques also do not identify which amplicons specifically bind to the LFS, which generate the visual readout. We aimed to standardize our characterization of LAMP products during assay development by using fluorescein amidite (FAM) and biotin-tagged loop forward and backward primers during assay development. A pvuII restriction enzyme digest is applied to the LAMP products. FAM-tagged bands are directly correlated with the LFS visual readout. We applied this assay development workflow for an HPV 16 assay using both plasmid DNA and clinical samples to demonstrate proof of concept for generalized assay development work. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00216-020-02702-9) contains supplementary material, which is available to authorized users.


Dilemas terapéuticos en la enfermedad por SARS-CoV-2, una emergencia y un reto para la geriatría


Announcement of Humanities and Medicine pages


Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China: Wu C, Chen X, Cai Y, et al. JAMA Intern Med. doi:10.1001/jamainternmed.2020.0994.


Digitalisierung in Zahlen


title: Sanal Flow Choking: A Paradigm Shift in Computational Fluid Dynamics Code Verification and Diagnosing Detonation and Hemorrhage in Real‐World Fluid‐Flow Systems

text: The discovery of Sanal flow choking is a scientific breakthrough and a paradigm shift in the diagnostics of the detonation/hemorrhage in real‐world fluid flow systems. The closed‐form analytical models capable of predicting the boundary‐layer blockage factor for both 2D and 3D cases at the Sanal flow choking for adiabatic and diabatic fluid flow conditions are critically reviewed here. The beauty and novelty of these models stem from the veracity that at the Sanal flow choking condition for diabatic flows all the conservation laws of nature are satisfied at a unique location, which allows for computational fluid dynamics (CFD) code verification. At the Sanal flow choking condition both the thermal choking and the wall‐friction‐induced flow choking occur at a single sonic fluid throat location. The blockage factor predicted at the Sanal flow choking condition can be taken as an infallible data for various in silico model verification, validation, and calibration. The 3D blockage factor at the Sanal flow choking is found to be 45.12% lower than the 2D case of a wall‐bounded diabatic fluid flow system with air as the working fluid. The physical insight of Sanal flow choking presented in this review article sheds light on finding solutions, through in silico experiments in base flow and nanoflows, for numerous unresolved problems carried forward over the centuries in physical, chemical, and biological sciences for humankind.


Rapid Responders: Plastics companies are stepping into the breach to design and deliver life‐saving PPE to healthcare workers


News/Resources


title: Framing consumer food demand responses in a viral pandemic

text: In this paper I explore several issues related to how the COVID‐19 pandemic might impact consumer demand for food. These impacts relate to the structure of preferences in the context of a pandemic, income and time constraints, and price effects. Discussion includes accounting for differential impacts of COVID‐19 on demand for food across sociodemographic characteristics, and several high‐level issues and observations related to where and how consumers shop and what they buy. My own thinking leads me to conclude that demand‐side factors will account for most of the changes we see in retail food market. These demand‐side effects will be dominated by income effects, the opportunity cost of time, and longer planning horizons on the part of consumers.


title: In Case You Haven't Heard…

text: Last week, the Blue Angels flew over the New York City area celebrating health care workers. More money in the Paycheck Protection Program is going out to “corporate America,” as Gov. Andrew Cuomo, who has become an international celebrity for his exhortations that the White House fund some of the health care workers and states, put it last week. “We don't need flyovers; we need help” is his message. Last week, more deaths from COVID‐19 were seen, and the opioid epidemic continued, as did reports of people quietly upping their happy hours to half‐days while isolated alone. Treatment centers are open, but where are the patients? Where is the money to fund the centers, to keep them from closing? How will America's addiction problem look when this is over — if it ever is — and how will we plan to take care of a problem that was number‐one in the headlines before the pandemic?


Do No Harm: Plastics are playing a major role in giving healthcare professionals the tools and capabilities they need to battle the COVID pandemic


title: Keep your community safe while COVID‐19 spreads globally

text: The spread of COVID‐19 globally has caused a high rate of sickness, death, and uncertainty, leading many U.S. colleges and universities to move instruction online for the time being and possibly through the end of the academic year and maybe beyond. When the global pandemic hit the United States, institutions struggled to quickly make decisions about how to deal with international students on campus, as well as how and when to pull American students studying abroad out of programs and bring them back to campus, without potentially spreading the disease through a healthy student population — and with how best to monitor and advise students in the wake of a global emergency.


Diabetes: Ein Risikofaktor bei COVID-19


SARS-CoV-2-Infektion vor ersten Symptomen


Schweigepflicht gilt auch bei COVID-19!


Digitale Revolution in der Diabetologie


Medizin


title: Working from home? Follow these tips for successful remote work

text: So you're asked to work from home as COVID‐19 cases spread.


title: Provide leadership to address economic impact of pandemic

text: “What should I be doing when I really don't know what will happen next? What can I learn?” Those are questions higher education leaders should be asking over the next few months about the impacts of the COVID‐19 pandemic, said Larenda Mielke, Vice President, Higher Education, at Kaufman Hall.


title: Be aware of how COVID‐19 could impact international students

text: The spread of COVID‐19 has impacted every aspect of college and university operations — and life in general. As you look ahead, consider ways the pandemic could impact your current and potential international students so you can implement plans to address the challenges.


title: CHINA AND WORLD OUTPUT IMPACT OF THE HUBEI LOCKDOWN DURING THE CORONAVIRUS OUTBREAK

text: Using a network approach, we estimate the output loss due to the lockdown of the Hubei province triggered by the coronavirus disease (COVID‐19). Based on our most conservative estimate, China suffers about 4% loss of output from labor loss, and global output drops by 1% per period due to the economic contraction in China. About 40% of the impact is indirect, coming from spillovers through the supply chain inside and outside China. (JEL E23, E24, F62)


Angry viruses make us sick: a child's depiction of SARS‐CoV‐2


title: Coronavirus: reducing the impact of quarantine

text: On the 26th February 2020, a meeting was held at the Royal Society of Medicine between key advisers in UK healthcare and law enforcement to discuss quarantine measures in response to the current COVID‐19 outbreak. This article is a brief summary of the comments and questions raised at the meeting.


title: Forecast in detail

text: The immediate fiscal consequences of the coronavirus pandemic are likely to be greater than those of the financial crisis in 2008–09. This reflects both the damage to the economy from containment measures and the cost of government policies to support incomes. But with gilt yields close to record lows and demand for UK government debt bolstered by BoE purchases, the interest cost of a temporary surge in the deficit should be modest.


text: The spread of COVID‐19 globally has caused a high rate of sickness, death, and uncertainty, leading many U.S. colleges and universities to move instruction online. When the global pandemic hit the United States, institutions struggled to quickly make decisions about how to deal with international students on campus, as well as how and when to pull American students studying abroad out of programs and bring them back to campus, without potentially spreading the disease through a healthy student population — and with how best to monitor and advise students in the wake of a global emergency.


title: Severe pain-related adverse events of percutaneous dilatational tracheostomy performed by a neurointensivist compared with conventional surgical tracheostomy in neurocritically ill patients

text: BACKGROUND: We evaluated severe pain-related adverse events (SAE) during the percutaneous dilatational tracheostomy (PDT) procedure performed by a neurointensivist and compared the outcomes with that of conventional surgical tracheostomy in neurocritically ill patients. METHODS: This was a retrospective and observational study of adult patients who were admitted to the neurosurgical intensive care unit between January 2014 and March 2018 and underwent tracheostomy. In this study, primary endpoints were incidence of SAE: cardiac arrest, arrhythmias, hypertension, hypotension, desaturation, bradypnea, or ventilatory distress. The secondary endpoint was procedure-induced complications. RESULTS: A total of 156 patients underwent tracheostomy during the study. Elective surgery of brain tumors (34.0%) and intracranial hemorrhage (20.5%) were the most common reasons for admission. The most common reasons for tracheostomy were difficult ventilator weaning or prolonged intubation (42.9%) and sedative reduction (23.7%). Tachycardia (30.1%) and hypertension (30.1%) were the most common SAE. Incidence of SAE was more common in conventional tracheostomy compared to PDT (67.1% vs. 42.3%, P = 0.002). The total duration of SAE (19.8 ± 23.0 min vs. 3.4 ± 5.3 min, P < 0.001) and procedural time (42.2 ± 21.8 min vs. 17.7 ± 9.2 min, P < 0.001) were longer in conventional tracheostomy compared to PDT. Multivariable adjustment revealed that only PDT by a neurointensivist significantly reduced the incidence of SAE by one third (adjusted odds ratio [OR]: 0.36, 95% confidence interval [CI]: 0.187–0.691). In addition, PDT by a neurointensivist deceased the duration of SAE by 8.64 min (β: -8.64, 95% CI: − 15.070 – -2.205, P = 0.009) and prolonging the procedure time by every one minute significantly increased the duration of SAE by 6.38 min (β: 6.38, 95% CI: 0.166–0.470, P < 0.001). Procedure-induced complications were more common in conventional tracheostomy compared to PDT (23.5% vs. 11.3%, P = 0.047). CONCLUSIONS: This retrospective and exploratory study of our single-center limited cohort of tracheostomy patients revealed that decreased SAE may be associated with short procedural time during the PDT procedure performed by a neurointensivist. It is proposed that PDT by a neurointensivist may be safe and feasible in neurocritically ill patients.


title: First record of besnoitiosis caused by Besnoitia bennetti in donkeys from the UK

text: BACKGROUND: The involvement of Besnoitia bennetti in skin pathologies was investigated in a series of 20 donkeys from the Donkey Sanctuary in England, in the 2013–2019 period. METHODS: The initial histopathological finding of Besnoitia cysts in skin lumps that were presumed to be sarcoids in 2013 triggered our cognisance of this parasite and resulted in identification of a total of 20 cases. Histopathological examination of surgical biopsy samples collected from 8 live donkeys and tissue specimens from 12 deceased donkeys at post-mortem examination revealed the presence of Besnoitia cysts in all 20 donkeys. The indirect fluorescent antibody test (IFAT) and immunoblotting analysis showed the presence of anti-Besnoitia antibodies in archived serum samples from 4 deceased donkeys. Additionally, infection was evidenced in one live donkey based on IFAT and immunoblot analysis of tissue fluid of a dermal mass containing Besnoitia cysts, and real-time (RT)-PCR analysis and microsatellite genotyping of DNA isolated from the tissue of the same dermal mass confirmed the infection specifically as B. bennetti. RESULTS: Both serological and microsatellite analyses confirmed the aetiology to be B. bennetti. Our findings suggested that in cases of skin masses such as sarcoids, the suspicion of B. bennetti infection should be borne in mind even when clinical and histopathology examination results are negative in order to avoid misdiagnosis. CONCLUSIONS: This case series documents, to our knowledge, the first report of B. bennetti infection in donkeys in the UK, indicating that donkey besnoitiosis has become noteworthy in the UK. Further investigations of the occurrence, epidemiological characteristics, and clinical manifestations of B. bennetti infection in donkeys and other equids are warranted. [Image: see text]


What can people think of doing when they have little money?


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title: Molecular Pathology Economics 101: an Overview of Molecular Diagnostics Coding, Coverage and Reimbursement

text: Widespread indications for use of molecular diagnostics in various aspects of clinical medicine have driven proliferation of testing. The rapid adoption and continuous technological evolution of molecular diagnostics have often strained the development and maintenance of a functional underlying framework of coding, coverage, and reimbursement policies, thereby presenting challenges to various stakeholders including molecular professionals, payers, and patients. A multidisciplinary working group convened by the Association for Molecular Pathology Economic Affairs Committee was tasked to describe the complex landscape of molecular pathology economics and highlight opportunities for member engagement. In this manuscript, on the basis of review and synthesis of government regulations and procedures, published payer policy documents, peer-reviewed literature, and expert consensus, the Working Group navigates the ecosystem of molecular pathology economics in terms of stakeholders, coding systems and processes, coverage policy determination, and pricing mechanisms. The composition and interrelatedness of various working groups and committees are emphasized in order to highlight the functional underpinnings of the system. Molecular professionals must be conversant in the language and complex inner workings of molecular pathology economics in order to lead successful, viable laboratories and advocate effectively for policy development on their behalf. This overview is provided to be a resource to molecular professionals as they navigate the reimbursement landscape.


Stephen M. Schwartz (1942–2020)


Adjunctive Therapies in ARDS: The Disconnect Between Clinical Trials and Clinical Practice


Mitteilungen der DGRh - Veranstaltungen der Rheumaakademie


title: Mapping the canine vector-borne disease risk in a Mediterranean area

text: BACKGROUND: The aim of this study was to determine exposure to vector-borne pathogens (VBPs) in populations of dogs living on Greek islands in the Ionian and Aegean seas. METHODS: In total, 1154 dogs with different lifestyles and of varying ages and breeds were randomly sampled and examined for the presence of clinical signs compatible with canine vector-borne diseases (CVBDs). Blood was collected from each individual animal. For the detection of antibodies against Leishmania spp., the WITNESS® Leishmania test was performed, and positive samples were further examined with indirect enzymatic immunoassay (ELISA). Antibodies to Borrelia burgdorferi, Ehrlichia canis or E. ewingii, as well as Anaplasma phagocytophilum or A. platys were investigated using the Snap® 4Dx® Plus test. Positive Ehrlichia spp. and Anaplasma spp. samples were further examined using an indirect ELISA for further identification of the species. RESULTS: In total, 25.6% of dogs were exposed to at least one of the pathogens investigated, with seroprevalences varying regionally. Of these seropositive dogs, 27.4% displayed clinical signs suggestive of CVBDs, such as cutaneous lesions, enlarged lymph nodes, pale mucous membranes, onychogryphosis and weight loss. The overall seroprevalence detected using the rapid tests was 15.3% for Leishmania spp., whereas 2.3% of the examined dogs were found to be positive for Anaplasma spp. and 7.5% for Ehrlichia spp. while B. burgdorferi was not detected. Twenty-four samples positive to A. phagocytophilum by ELISA were analysed by PCR for the presence of Anaplasma DNA. PCR and sequencing results showed the presence of A. platys DNA in 4 samples and E. canis DNA in 4 samples. The remaining samples (66.7%) were negative. CONCLUSIONS: In the present study, exposure of dogs to VBPs was shown in the geographical areas investigated. Results confirm that on Greek islands VBPs represent a constant health risk for both native and visiting dogs, suggesting the presence of distinct “hot-spots” of VBP infections on different islands. In order to reduce the risk of transmission and the spread to non-endemic regions, the protection of dogs through use of repellents and vaccines, together with owner education, seem to be of paramount importance. [Image: see text]


title: Minimally invasive beating heart technique for mitral valve surgery in patients with previous sternotomy and giant left ventricle

text: PURPOSE: To analyze the efficacy of minimally invasive beating heart technique for mitral valve surgery in the cardiac patients with previous sternotomy and giant left ventricle. METHODS: Eighty cardiac patients with previous sternotomy and giant left ventricle according to the diagnostic criteria that left ventricular end diastolic diameter (LVEDD) was ≥70 mm, who underwent mitral valve surgery at our center from January 2006 to January 2019 were analyzed. We divided all patients into minimally invasive beating heart technique group (n = 30) and conventional median resternotomy arrested heart technique group (n = 50) according to the surgical methods. Preoperative, intraoperative, and postoperative variables were compared between two groups. RESULTS: Minimally invasive beating heart technique compared to the conventional median resternotomy arrested heart technique for mitral valve surgery in the cardiac patients with previous sternotomy and giant left ventricle had significant differences in operation time(P = 0.002), cardiopulmonary bypass (CPB) time(P < 0.001), intraoperative blood loss(P < 0.001), postoperative transfusion ratio(P = 0.01), postoperative transfusion amount(P < 0.001), postoperative drainage volume(P = 0.001), extubation time(P = 0.04), intensive care unit (ICU) stay time(P = 0.04) and postoperative hospital stay time(P < 0.001), but no significant differences in re-exploration for bleeding, postoperative 30-day mortality, postoperative complications and 6 months postoperative echocardiographic parameters. CONCLUSIONS: Using the method of minimally invasive beating heart technique for mitral valve surgery in the cardiac patients with previous sternotomy and giant left ventricle is effective and reliable, meanwhile reduce the operation time and CPB time, decrease the transfusion ratio and transfusion amount, shorten postoperative ICU stay and hospital stay time, promote the early extubation so that accelerate the patients’ early recovery. All of these show a benefit of minimally invasive beating heart technique compared to conventional median resternotomy arrested heart technique.


title: Beruflich erworbene MRSA-Besiedelung in der berufsdermatologischen Begutachtung (BK-Nr. 3101): Auswertung der DGUV BK-Dokumentation und Gutachtenfall mit arbeitsbedingter MRSA-getriggerter atopischer Dermatitis

text: BACKGROUND: Person-to-person transmitted infectious diseases can cause occupational diseases (OD). These are subsumed as BK-No. 3101 in the German list of OD which applies for individuals with a considerably higher risk for infection as a consequence of their professional activity compared to the general population. OBJECTIVES: The special medical and insurance law aspects of a work-related MRSA colonization are presented using the example of an expert opinion case and an evaluation of the BK reports of suspected occupational disease (BK No. 3101) of the German Social Accident Insurance (DGUV). PATIENTS AND METHODS: The BK documentation of the DGUV from 2007–2012 and the patient cohort from the Department of Dermatology, University Hospital Erlangen, presenting for expert assessment from 2007–2012 were retrospectively analysed for human-to-human transmitted infectious diseases of the skin (BK-No. 3101). RESULTS: Person-to-person transmission of infectious diseases of the skin is rare in the field of occupational dermatology. In the DGUV cohort, suspected BK-No. 3101cases amounted to 2.6% of all notified cases; recognized BK-No. 3101 cases accounted for 4.2% of all recognized cases, amongst which 9 were caused by MRSA. In contrast to a symptomatic infection, an asymptomatic MRSA colonization is not being recognized as BK-No. 3101. Bacterial superantigens can trigger atopic dermatitis (AD). In particular cases, occupationally acquired MRSA can elicit AD and may justify classification as an OD (BK-No. 3101). CONCLUSIONS: Early detection of MRSA colonization and eradication are necessary for rehabilitation. Management of skin diseases due to infectious diseases within the framework of OD is presented.


title: Identification of genetic loci associated with higher resistance to pancreas disease (PD) in Atlantic salmon (Salmo salar L.)

text: BACKGROUND: Pancreas disease (PD) is a contagious disease caused by salmonid alphavirus (SAV) with significant economic and welfare impacts on salmon farming. Previous work has shown that higher resistance against PD has underlying additive genetic components and can potentially be improved through selective breeding. To better understand the genetic basis of PD resistance in Atlantic salmon, we challenged 4506 smolts from 296 families of the SalmoBreed strain. Fish were challenged through intraperitoneal injection with the most virulent form of the virus found in Norway (i.e., SAV3). Mortalities were recorded, and more than 900 fish were further genotyped on a 55 K SNP array. RESULTS: The estimated heritability for PD resistance was 0.41 ± 0.017. The genetic markers on two chromosomes, ssa03 and ssa07, showed significant associations with higher disease resistance. Collectively, markers on these two QTL regions explained about 60% of the additive genetic variance. We also sequenced and compared the cardiac transcriptomics of moribund fish and animals that survived the challenge with a focus on candidate genes within the chromosomal segments harbouring QTL. Approximately 200 genes, within the QTL regions, were found to be differentially expressed. Of particular interest, we identified various components of immunoglobulin-heavy-chain locus B (IGH-B) on ssa03 and immunoglobulin-light-chain on ssa07 with markedly higher levels of transcription in the resistant animals. These genes are closely linked to the most strongly QTL associated SNPs, making them likely candidates for further investigation. CONCLUSIONS: The findings presented here provide supporting evidence that breeding is an efficient tool for increasing PD resistance in Atlantic salmon populations. The estimated heritability is one of the largest reported for any disease resistance in this species, where the majority of the genetic variation is explained by two major QTL. The transcriptomic analysis has revealed the activation of essential components of the innate and the adaptive immune responses following infection with SAV3. Furthermore, the complementation of the genomic with the transcriptomic data has highlighted the possible critical role of the immunoglobulin loci in combating PD virus.


title: Introduction to Computer Network Vulnerabilities

text: System vulnerabilities are weaknesses in the software or hardware on a server or a client that can be exploited by a determined intruder to gain access to or shut down a network. Vulnerabilities exist not only in the hardware and software that constitute a computer system but also in policies and procedures, especially security policies and procedures, that are used in a computer network system and in users and employees of the computer network systems. Vulnerabilities can be found in so many areas in a network system and are indeed anything in a computer network that has the potential to cause or be exploited for an advantage. This chapter explores the sources and assessment of a computer network system’s vulnerabilities.


Now Is the Time for a Rights-Based Approach to Social Work Practice


title: What is the research evidence for antibiotic resistance exposure and transmission to humans from the environment? A systematic map protocol

text: BACKGROUND: Antimicrobial resistance (AMR) is a public health crisis that is predicted to cause 10 million deaths per year by 2050. The environment has been implicated as a reservoir of AMR and is suggested to play a role in the dissemination of antibiotic resistance genes (ARGs). Currently, most research has focused on measuring concentrations of antibiotics and characterising the abundance and diversity of ARGs and antibiotic resistant bacteria (ARB) in the environment. To date, there has been limited empirical research on whether humans are exposed to this, and whether exposure can lead to measureable impacts on human health. Therefore, the objective of this work is to produce two linked systematic maps to investigate previous research on exposure and transmission of AMR to humans from the environment. The first map will investigate the available research relating to exposure and transmission of ARB/ARGs from the environment to humans on a global scale and the second will investigate the prevalence of ARB/ARGs in various environments in the UK. These two maps will be useful for policy makers and research funders to identify where there are significant gluts and gaps in the current research, and where more primary and synthesis research needs to be undertaken. METHODS: Separate search strategies will be developed for the two maps. Searches will be run in 13 databases, and grey literature will be sought from key websites and engagement with experts. Hits will be managed in EndNote and screened in two stages (title/abstract then full text) against predefined inclusion criteria. A minimum of 10% will be double screened with ongoing consistency checking. All included studies will have data extracted into a bespoke form designed and piloted for each map. Data to be extracted will include bibliographic details, study design, location, exposure source, exposure route, health outcome (Map 1); and prevalence/percentage of ARB/ARG (Map 2). No validity appraisal will be undertaken. Results will be tabulated and presented narratively, together with graphics showing the types and areas of research that has been undertaken and heatmaps for key exposure-health outcomes (Map 1) and exposure-prevalence (Map 2).


title: Determinants of neonatal mortality at neonatal intensive care unit in Northeast Ethiopia: unmatched case-control study

text: BACKGROUND: Globally, in 2016, about 38% and 3% of all neonatal death were recorded in sub-Saharan Africa and Ethiopia, respectively. In the same year, 47 neonates out of 1000 live births were not surviving in the first 28 days of age in the Amhara region, Ethiopia. Despite the highest burden of neonatal death in the region, specific or the proximate determinants of neonatal death in the neonatal intensive care unit were not well identified. OBJECTIVE: This study aimed to identify the determinants of neonatal mortality at neonatal intensive care unit in Dessie Referral Hospital, Northeast Ethiopia. METHODS: An institution-based unmatched case-control study was conducted on neonates admitted to the neonatal intensive care unit of Dessie Referral Hospital, from January 1, 2016, to December 30, 2017. A total of 390 charts (130 cases and 260 controls) were selected by simple random sampling technique. The data were abstracted from the facility-based data abstraction form. A binary logistic regression analysis was fitted to identify the determinants of neonatal mortality. RESULTS: Pregnancy-induced hypertension (AOR = 4.57; 95% CI 1.45–14.43), prolonged rupture of membrane (AOR = 2.04; 95% CI 1.13–3.68), very low birth weight (AOR = 7.00; 95% CI 2.10–23.35), and low birth weight (AOR = 2.12; 95% CI 1.10–4.20) were identified factors. Moreover, respiratory distress syndrome (AOR = 3.61; 95% CI 1.10–12.04), perinatal asphyxia (AOR = 2.27; 95% CI 1.18–4.39), meconium aspiration syndrome (AOR = 2.35; 95% CI 1.12–4.97), and infection (AOR = 2.26; 95% CI 1.34–3.82) were also significantly associated with neonatal death. CONCLUSIONS: Pregnancy-induced hypertension, prolonged rupture of membrane, low birth weight, respiratory distress syndrome, perinatal asphyxia, meconium aspiration syndrome, and infections were the major determinants of neonatal mortality. Therefore, special attention will be given to small and sick babies. Moreover, early anticipation of complications and management of mothers who had pregnancy-induced hypertension and prolonged rupture of the membrane would save neonates.