Background

The mainstay of toxoplasmosis treatment targets the folate biosynthetic pathways and has not changed for the last 50 years. The activity of these chemotherapeutic agents is restricted to one lifecycle stage of Toxoplasma gondii, they have significant toxicity, and the impending threat of emerging resistance to these agents makes the discovery of new therapies a priority. We now demonstrate that auranofin, an orally administered gold containing compound that was FDA approved for treatment of rheumatoid arthritis, has activity against Toxoplasma gondii in vitro (IC50 = 0.28 µM) and in vivo (1 mg/kg).

Methods/principal findings

Replication within human foreskin fibroblasts of RH tachyzoites was inhibited by auranofin. At 0.4 µM, auranofin inhibited replication, as measured by percent infected fibroblasts at 24 hrs, (10.94% vs. 24.66% of controls; p = 0.0003) with no effect on parasite invasion (16.95% vs. 12.91% p = 0.4331). After 18 hrs, 62% of extracellular parasites treated with auranofin were non-viable compared to control using an ATP viability assay (p = 0.0003). In vivo, a previously standardized chicken embryo model of acute toxoplasmosis was used. Fourteen day old chicken embryos were injected through the chorioallantoic vein with 1×104 tachyzoites of the virulent RH strain. The treatment group received one dose of auranofin at the time of inoculation (1 mg/kg estimated body weight). On day 5, auranofin-treated chicken embryos were 100% protected against death (p = 0.0002) and had a significantly reduced parasite load as determined by histopathology, immunohistochemistry and by the number of parasites quantified by real-time PCR.

Conclusions

These results reveal in vitro and in vivo activity of auranofin against T. gondii, suggesting that it may be an effective alternative treatment for toxoplasmosis.

Natural Language Processing (NLP) is essential for concept extraction from narrative text in electronic health records (EHR). To extract numerous and diverse concepts, such as data elements (i.e., important concepts related to a certain medical condition), a plausible solution is to combine various NLP tools into an ensemble to improve extraction performance. However, it is unclear to what extent ensembles of popular NLP tools improve the extraction of numerous and diverse concepts. Therefore, we built an NLP ensemble pipeline to synergize the strength of popular NLP tools using seven ensemble methods, and to quantify the improvement in performance achieved by ensembles in the extraction of data elements for three very different cohorts. Evaluation results show that the pipeline can improve the performance of NLP tools, but there is high variability depending on the cohort.

Although toxoplasmosis is one of the most common parasitic infections worldwide, therapeutic options remain limited. Cathepsins, proteases that play key roles in the pathogenesis of toxoplasmosis and many other protozoan infections, are important potential therapeutic targets. Because both TgCPB and TgCPL play a role in T. gondii invasion, we evaluated the efficacy of the potent, irreversible vinyl sulfone inhibitor, K11777 (N-methyl-piperazine-Phe-homoPhe-vinylsulfone-phenyl). The inhibitor's toxicity and pharmacokinetic profile have been well-studied because of its in vitro and in vivo activity against a number of parasites. We found that it inhibited both TgCPB (EC50 = 114 nM) and TgCPL (EC50 = 71 nM) in vitro. K11777 also inhibited invasion of human fibroblasts by RH tachyzoites by 71% (p = 0.003) and intracellular replication by >99% (p<0.0001). In vivo, a single dose of K11777 led to 100% survival of chicken embryos in an model of acute toxoplasmosis (p = 0.015 Cox regression analysis). Therefore, K11777 shows promise as a novel therapeutic agent in the treatment of toxoplasmosis, and may prove to be a broadly effective anti-parasitic agent.

Objective

Delayed diagnosis of Kawasaki disease (KD) may lead to serious cardiac complications. We sought to create and test the performance of a natural language processing (NLP) tool, the KD-NLP, in the identification of emergency department (ED) patients for whom the diagnosis of KD should be considered.

Methods

We developed an NLP tool that recognizes the KD diagnostic criteria based on standard clinical terms and medical word usage using 22 pediatric ED notes augmented by Unified Medical Language System vocabulary. With high suspicion for KD defined as fever and three or more KD clinical signs, KD-NLP was applied to 253 ED notes from children ultimately diagnosed with either KD or another febrile illness. We evaluated KD-NLP performance against ED notes manually reviewed by clinicians and compared the results to a simple keyword search.

Results

KD-NLP identified high-suspicion patients with a sensitivity of 93.6% and specificity of 77.5% compared to notes manually reviewed by clinicians. The tool outperformed a simple keyword search (sensitivity = 41.0%; specificity = 76.3%).

Conclusions

KD-NLP showed comparable performance to clinician manual chart review for identification of pediatric ED patients with a high suspicion for KD. This tool could be incorporated into the ED electronic health record system to alert providers to consider the diagnosis of KD. KD-NLP could serve as a model for decision support for other conditions in the ED.