A Two-Biomarker Model Predicts Mortality in the Critically Ill with Sepsis.

RATIONALE: Improving the prospective identification of patients with systemic inflammatory response syndrome (SIRS) and sepsis at low risk for organ dysfunction and death is a major clinical challenge. OBJECTIVES: To develop and validate a multibiomarker-based prediction model for 28-day mortality in critically ill patients with SIRS and sepsis. METHODS: A derivation cohort (n = 888) and internal test cohort (n = 278) were taken from a prospective study of critically ill intensive care unit (ICU) patients meeting two of four SIRS criteria at an academic medical center for whom plasma was obtained within 24 hours. The validation cohort (n = 759) was taken from a prospective cohort enrolled at another academic medical center ICU for whom plasma was obtained within 48 hours. We measured concentrations of angiopoietin-1, angiopoietin-2, IL-6, IL-8, soluble tumor necrosis factor receptor-1, soluble vascular cell adhesion molecule-1, granulocyte colony-stimulating factor, and soluble Fas. MEASUREMENTS AND MAIN RESULTS: We identified a two-biomarker model in the derivation cohort that predicted mortality (area under the receiver operator characteristic curve [AUC], 0.79; 95% confidence interval [CI], 0.74-0.83). It performed well in the internal test cohort (AUC, 0.75; 95% CI, 0.65-0.85) and the external validation cohort (AUC, 0.77; 95% CI, 0.72-0.83). We determined a model score threshold demonstrating high negative predictive value (0.95) for death. In addition to a low risk of death, patients below this threshold had shorter ICU length of stay, lower incidence of acute kidney injury, acute respiratory distress syndrome, and need for vasopressors. CONCLUSIONS: We have developed a simple, robust biomarker-based model that identifies patients with SIRS/sepsis at low risk for death and organ dysfunction

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Instant messaging and presence management in mobile ad-hoc networks

peer-reviewedThe combination of real-time message delivery and presence awareness has to lead the rapid rise in popularity of Instant Messaging (IM) in recent years. The extension of IM to mobile ad-hoc networks certainly offers considerable potential. However, the dynamic topology and decentralized nature of these networks requires several major issues to be addressed. Specifically, difficulties exist in providing an effective reliable service in the absence of a continuously available server. We present here the Dawn IM system, which takes a decentralized approach to bringing the functionality inherent in fixed-network IM systems to an ad-hoc environment. In addition we discuss a test-bed implementation that supports collaboration between users equipped with handheld devices

Overlay networks : a scalable alternative for P2P

peer-reviewedOverlay networks create a structured virtual topology above the basic transport protocol level that facilitates deterministic search and guarantees convergence. Overlay networks are evolving into a critical component for self-organizing systems. Here we outline the differences between flooding-style and overlay networks, and offer specific examples of how researchers are applying the latter to problems requiring high-speed, self-organizing network topologies

Analyzing the vulnerability of wireless sensor networks to a malicious matched protocol attack

Safety critical, Internet of Things (IoT) and space-based applications have recently begun to adopt wireless networks based on commercial off the shelf (COTS) devices and standardized protocols, which inherently establishes the security challenge of malicious intrusions. Malicious intrusions can cause severe consequences if undetected, including, complete denial of services. Particularly, any safety critical application requires all services to operate correctly, as any loss can be detrimental to safety and/or privacy. Therefore, in order for these safety critical services to remain operational and available, any and all intrusions need to be detected and mitigated. Whilst intrusion detection is not a new research area, new vulnerabilities in wireless networks, especially wireless sensor networks (WSNs), can be identified. In this paper, a specific vulnerability of WSNs is explored, termed here the matched protocol attack. This malicious attack uses protocol-specific structures to compromise a network using that protocol. Through attack exploration, this paper provides evidence that traditional spectral techniques are not sufficient to detect an intrusion using this style of attack. Furthermore, a ZigBee cluster head network, which co-exists with ISM band services, consisting of XBee COTS devices is utilized, along with a real time spectrum analyzer, to experimentally evaluate the effect of matched protocol interference on a realistic network model. Results of this evaluation are provided in terms of device errors and spectrum use. This malicious challenge is also examined through Monte-Carlo simulations. A potential detection technique, based on coarse inter-node distance measurements, which can theoretically be used to detect matched protocol interference and localize the origin of the source, is also suggested as a future progression of this work. Insights into how this attack style preys on some of the main security risks of any WSN (interoperability, device limitations and operation in hostile environments) are also provided

Tracing Individual Public Transport Customers from an Anonymous Transaction Database

Data mining concepts are used frequently throughout the transportation research sector. This article examines the concept of the market basket technique as a means of gaining more insight into public transport users’ demands. The article proposes a method that uses various data attributes of passenger records to infer the same customer in a different week (i.e., attempts to track the same customer from week to week). The general idea behind the measure is that if two records are considered similar, ideally every trip in one customer record should have a close counterpart in the other record. The research develops a similarity function designed to maximize the percentage of positive ticket identification over a number of weeks. Once similarity has been established, customer travel patterns can be useful in helping the operator identify new routes, new timetables, and strategic decisions in relation to satisfying public transport customer demands

Tourists\u27 intention to visit food tourism destination: a conceptual framework

In recent years, food tourism has emerged as an area of interest for both tourism researchers and practitioners. However, research in food tourism is limited and there is a lack of empirical studies into tourists¿ intentions to visit a food tourism destination. This paper attempts to build a conceptual framework based on the original Theory of Planned Behavior (TPB) by modifying the TPB model to include three additional constructs: motivation, involvement and past behavior towards visiting a food tourism destination. The influence of socio-demographic variables is also examined in this model. Since very few studies have been published in this particular area, this provides a theoretical base for future studies in the field of food tourism and destination choice

In-hospital adverse drug reactions in older adults; prevalence, presentation and associated drugs—a systematic review and meta-analysis

Background: the prevalence of adverse drug reactions (ADRs) in hospitalised older patients, their clinical presentations, causative drugs, severity, preventability and measurable outcomes are unclear, ADRs being an increasing challenge to older patient safety. Methods: we systematically searched PubMed, Embase, EBSCO-CINAHL, the Cochrane Library, ‘rey’ literature and relevant systematic review bibliographies, published from database inception to March 2020. We included any study reporting occurrence of in-hospital ADRs as primary or secondary outcomes in hospitalised older adults (mean age ≥ 65 years). Two authors independently extracted relevant information and appraised studies for bias. Study characteristics, ADR clinical presentations, causative drugs, severity, preventability and clinical outcomes were analysed. Study estimates were pooled using random-effects meta-analytic models. Results: from 2,399 abstracts, we undertook full-text screening in 286, identifying 27 studies (29 papers). Final analysis yielded a pooled ADR prevalence of 16% (95%CI 12–22%, I2 98%,τ2 0.8585), in a population of 20,153 hospitalised patients aged ≥65 years of whom 2,479 patients experienced ≥ one ADR. ADR ascertainment was highly heterogeneous. Almost 48.3% of all ADRs involved five presentations: fluid/electrolyte disturbances (17.3%), gastrointestinal motility/defaecation disorders (13.3%), renal disorders (8.2%), hypotension/blood pressure dysregulation disorders/shock (5.5%) and delirium (4.1%). Four drug classes accounted for 57.8% of causative medications i.e. diuretics (19.8%), anti-bacterials (14.8%), antithrombotic agents (12.2%) and analgesics (10.9%). Pooled analysis of severity was not feasible. Four studies reported the majority of ADRs as preventable (55–95%). Conclusions: on average, 16% of hospitalised older patients experience significant ADRs, varying in severity and mostly preventable, with commonly prescribed drug classes accounting for most ADRs

A Rapid Viability and Drug‑Susceptibility Assay Utilizing Mycobacteriophage as an Indicator of Drug Susceptibilities of Anti‑TB Drugs against Mycobacterium smegmatis mc2 155

Background: A rapid in-house TM4 mycobacteriophage-based assay, to identify multidrug resistance against various anti-tuberculosis drugs, using the fast-growing Mycobacterium smegmatis mc2 155 in a microtiter plate format was evaluated, based on phage viability assays. Methods: A variety of parameters were optimized before the study including the minimum incubation time for the drugs, phage and M. smegmatis mc2 155 to be in contact. An increase in phage numbers over 2 h was indicative that M. smegmatis mc2 155 is resistant to the drugs under investigation, however when phage numbers remained static, M. smegmatis mc2 155 found to be sensitive to the drug. Results: The study confirmed that the data are statistically significant and that M. smegmatis mc2 155 is, in fact, sensitive to isonazid, iifampicin, pyranzaimide, and ethambutol as phage numbers doubled over 2 h (P = 0.015, 0.018, 0.014, and 0.020). The study also confirmed that M. smegmatis mc2 155 is resistant to the drugs ampicillin, erythromycin, amoxicillin streptomycin as phage numbers remain static over the same 2 h period (P = 0.028, 0.052, 0.049, and 0.04). This drug-susceptibility profiling of eight different drugs against M. smegmatis mc2 155 was detected in as little as 1½ days with a cost of ~ one euro and fifteen cent to test four drugs. Conclusion: This test is rapid to perform and will have widespread applications in drug-susceptibility testing of other members of the mycobacterial genus. In addition, the platform could also be used as a tool for high-throughput screening of novel antimycobacterial drugs. The main assets of this assay include its relatively cheap cost, versatility, and quick turnaround time