1,804 research outputs found

    When prosthetic joint infection may lead to premalignant colorectal lesion detection

    Get PDF
    Osteoarthritis (OA) is a common musculoskeletal disorder that affects millions of people worldwide, and total knee arthroplasty (TKA) is a common treatment for advanced OA. However, joint replacement surgeries may lead to complications such as deep vein thrombosis (DVT), surgical site infection, and prosthetic joint infection (PJI). Our objective is to discuss a Streptococcus bovis group (SBG) PJI case after TKA and its possible consequences in clinical practice. We describe a 67-year-old female who underwent TKA and developed initial complications including wound hematoma, symptomatic anemia, and acute DVT. Further investigations because of knee pain persistence and inflammatory signs post TKA revealed the presence of Staphylococcus aureus in the synovial and scar tissues from the knee and SBG in the periprosthetic membrane from the revision surgery, as well as mitral infective endocarditis and a large stenosing villous polypoid lesion in the ascending colon. SBG osteoarticular infection post TKA is a rare condition, but it may be associated with severe diseases. This article highlights the link between SBG and colorectal cancer (CRC) and emphasizes the importance of an echocardiogram and a colonoscopy for early detection and prompt treatment of infective endocarditis and CRC. This diagnostic workup should be performed even in the absence of symptoms, for early diagnosis and increased chance of cure. A multidisciplinary approach, involving orthopedists, infectious disease specialists, cardiologists, and gastroenterologists, among others, is advised to effectively manage SBG infections and improve patient outcomes

    The BLue Amazon Brain (BLAB): A Modular Architecture of Services about the Brazilian Maritime Territory

    Full text link
    We describe the first steps in the development of an artificial agent focused on the Brazilian maritime territory, a large region within the South Atlantic also known as the Blue Amazon. The "BLue Amazon Brain" (BLAB) integrates a number of services aimed at disseminating information about this region and its importance, functioning as a tool for environmental awareness. The main service provided by BLAB is a conversational facility that deals with complex questions about the Blue Amazon, called BLAB-Chat; its central component is a controller that manages several task-oriented natural language processing modules (e.g., question answering and summarizer systems). These modules have access to an internal data lake as well as to third-party databases. A news reporter (BLAB-Reporter) and a purposely-developed wiki (BLAB-Wiki) are also part of the BLAB service architecture. In this paper, we describe our current version of BLAB's architecture (interface, backend, web services, NLP modules, and resources) and comment on the challenges we have faced so far, such as the lack of training data and the scattered state of domain information. Solving these issues presents a considerable challenge in the development of artificial intelligence for technical domains

    Consumer Complaints and Company Market Value

    Get PDF
    Consumer complaints affect company market value and common sense suggests that a negative impact is expected. However, do complaints always negatively impact company market value? We hypothesize in this study that complaints may have a non-linear effect on market value. Positive (e.g. avoiding high costs to solve complaints) and negative (e.g. speedy and intense diffusion) tradeoffs may occur given the level of complaints. To test our non-linear hypothesis, a panel data was collected from cell phone service providers from 2005 to 2013. The results supported our tradeoff rationale. Low levels of complaints allow for companies to increase market value, while high levels of complaints cause increasing harm to market value. The sample, model and period considered in this study, indicates a level of 0.49 complaints per thousand consumers as the threshold for a shift in tradeoffs. The effects on market value become increasingly negative when trying to make reductions to move below this level, due to negative tradeoffs

    The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

    Get PDF
    BACKGROUND: Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them.RESULTS:A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew's Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89 and the best AUC iP/R was 68. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing systems against manually generated annotations done by curators from the BioGRID and MINT databases. The highest AUC iP/R achieved by any run was 53, the best MCC score 0.55. In case of competitive systems with an acceptable recall (above 35) the macro-averaged precision ranged between 50 and 80, with a maximum F-Score of 55. CONCLUSIONS: The results of the ACT task of BioCreative III indicate that classification of large unbalanced article collections reflecting the real class imbalance is still challenging. Nevertheless, text-mining tools that report ranked lists of relevant articles for manual selection can potentially reduce the time needed to identify half of the relevant articles to less than 1/4 of the time when compared to unranked results. Detecting associations between full text articles and interaction detection method PSI-MI terms (IMT) is more difficult than might be anticipated. This is due to the variability of method term mentions, errors resulting from pre-processing of articles provided as PDF files, and the heterogeneity and different granularity of method term concepts encountered in the ontology. However, combining the sophisticated techniques developed by the participants with supporting evidence strings derived from the articles for human interpretation could result in practical modules for biological annotation workflows

    The gene normalization task in BioCreative III

    Get PDF
    BACKGROUND: We report the Gene Normalization (GN) challenge in BioCreative III where participating teams were asked to return a ranked list of identifiers of the genes detected in full-text articles. For training, 32 fully and 500 partially annotated articles were prepared. A total of 507 articles were selected as the test set. Due to the high annotation cost, it was not feasible to obtain gold-standard human annotations for all test articles. Instead, we developed an Expectation Maximization (EM) algorithm approach for choosing a small number of test articles for manual annotation that were most capable of differentiating team performance. Moreover, the same algorithm was subsequently used for inferring ground truth based solely on team submissions. We report team performance on both gold standard and inferred ground truth using a newly proposed metric called Threshold Average Precision (TAP-k). RESULTS: We received a total of 37 runs from 14 different teams for the task. When evaluated using the gold-standard annotations of the 50 articles, the highest TAP-k scores were 0.3297 (k=5), 0.3538 (k=10), and 0.3535 (k=20), respectively. Higher TAP-k scores of 0.4916 (k=5, 10, 20) were observed when evaluated using the inferred ground truth over the full test set. When combining team results using machine learning, the best composite system achieved TAP-k scores of 0.3707 (k=5), 0.4311 (k=10), and 0.4477 (k=20) on the gold standard, representing improvements of 12.4%, 21.8%, and 26.6% over the best team results, respectively. CONCLUSIONS: By using full text and being species non-specific, the GN task in BioCreative III has moved closer to a real literature curation task than similar tasks in the past and presents additional challenges for the text mining community, as revealed in the overall team results. By evaluating teams using the gold standard, we show that the EM algorithm allows team submissions to be differentiated while keeping the manual annotation effort feasible. Using the inferred ground truth we show measures of comparative performance between teams. Finally, by comparing team rankings on gold standard vs. inferred ground truth, we further demonstrate that the inferred ground truth is as effective as the gold standard for detecting good team performance

    The Trypanosoma cruzi Virulence Factor Oligopeptidase B (OPBTc) Assembles into an Active and Stable Dimer

    Get PDF
    Oligopeptidase B, a processing enzyme of the prolyl oligopeptidase family, is considered as an important virulence factor in trypanosomiasis. Trypanosoma cruzi oligopeptidase B (OPBTc) is involved in host cell invasion by generating a Ca2+-agonist necessary for recruitment and fusion of host lysosomes at the site of parasite attachment. The underlying mechanism remains unknown and further structural and functional characterization of OPBTc may help clarify its physiological function and lead to the development of new therapeutic molecules to treat Chagas disease. In the present work, size exclusion chromatography and analytical ultracentrifugation experiments demonstrate that OPBTc is a dimer in solution, an association salt and pH-resistant and independent of intermolecular disulfide bonds. The enzyme retains its dimeric structure and is fully active up to 42°C. OPBTc is inactivated and its tertiary, but not secondary, structure is disrupted at higher temperatures, as monitored by circular dichroism and fluorescence spectroscopy. It has a highly stable secondary structure over a broad range of pH, undergoes subtle tertiary structure changes at low pH and is less stable under moderate ionic strength conditions. These results bring new insights into the structural properties of OPBTc, contributing to future studies on the rational design of OPBTc inhibitors as a promising strategy for Chagas disease chemotherapy

    The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

    Get PDF
    AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

    Autoantibodies against type I IFNs in patients with life-threatening COVID-19

    Get PDF
    Interindividual clinical variability in the course of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is vast. We report that at least 101 of 987 patients with life-threatening coronavirus disease 2019 (COVID-19) pneumonia had neutralizing immunoglobulin G (IgG) autoantibodies (auto-Abs) against interferon-w (IFN-w) (13 patients), against the 13 types of IFN-a (36), or against both (52) at the onset of critical disease; a few also had auto-Abs against the other three type I IFNs. The auto-Abs neutralize the ability of the corresponding type I IFNs to block SARS-CoV-2 infection in vitro. These auto-Abs were not found in 663 individuals with asymptomatic or mild SARS-CoV-2 infection and were present in only 4 of 1227 healthy individuals. Patients with auto-Abs were aged 25 to 87 years and 95 of the 101 were men. A B cell autoimmune phenocopy of inborn errors of type I IFN immunity accounts for life-threatening COVID-19 pneumonia in at least 2.6% of women and 12.5% of men
    corecore