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Fragrances are the most common cause of cosmetic contact allergy. Up-to-date information on contact allergy frequencies and relevance aids primary and secondary preventive measures.

To determine the prevalence, associated factors, and concomitant reactions in fragrance allergy among Thais.

This retrospective study collected data from 2012 to 2019. The patient characteristics of fragrance and nonfragrance allergy groups were compared. Concurrent positive reactions to fragrance allergens (fragrance mix [FM] I, FM II, Myroxylon pereirae resin and hydroxyisohexyl 3-cyclohexene carboxaldehyde) and other baseline-series allergens were analysed.

Of 1032 patients, 175 (17.0%) had fragrance allergy, with 57.7% of clinical relevance. FM I showed the highest prevalence (9.4%). The associated factors were being elderly, lesions on the extremities, metal allergy history, and long dermatitis duration. Contact allergies to epoxy resin and Compositae plants were significantly associated with fragrance allergy with an odds ratio of 5.95 (95% confidence interval [CI] 5.21-6.80) and an odds ratio of 4.42 (95% CI 1.58-12.36), respectively. No significant associations between colophonium (previously proposed as a fragrance marker) and fragrance allergens were found.

The prevalence of fragrance contact allergy remains high and should be considered in old patients presenting with long-standing eczema on the extremities. Unlike reports from other countries, varied, significant, concomitant reactions were observed.

The prevalence of fragrance contact allergy remains high and should be considered in old patients presenting with long-standing eczema on the extremities. Unlike reports from other countries, varied, significant, concomitant reactions were observed.We compared self-collected oral fluid swab specimens with and without clinician supervision, clinician-supervised self-collected mid-turbinate (nasal) swab specimens, and clinician-collected nasopharyngeal swab specimens for the detection of SARS-CoV-2. Supervised oral fluid and nasal swab specimens performed similarly to clinician-collected nasopharyngeal swab specimens. No sample type could detect SARS-CoV-2 infections amongst all positive participants.Tosedostat is an orally administered metalloenzyme inhibitor with antiproliferative and antiangiogenic activity against hematological and solid human cancers. Clinical activity has been demonstrated in relapsed acute myeloid leukemia (AML). Thirty-three elderly patients with AML (median age, 75 years) received 120 mg tosedostat orally once daily combined with subcutaneous low-dose cytarabine (20 mg twice per day for 10 days, up to 8 cycles), until disease progression. Induction mortality was 12%. According to an intention-to-treat analysis, the complete remission (CR) rate was 48.5%, and thus the primary end point of the study was reached (expected CR, 25%). The partial remission rate was 6.1%, with an overall response rate of 54.5%. Furthermore, 4 of 33 patients had stable disease (median 286 days). The median progression-free survival and overall survival (OS) were 203 days and 222 days, respectively. Responding patients had a longer median OS than nonresponding patients (P = .001). A microarray analysis performed in 29 of 33 patients identified 188 genes associated with clinical response (CR vs no CR). Three of them (CD93, GORASP1, CXCL16) were validated by quantitative polymerase chain reaction, which correctly classified 83% of the patients. Specifically, CR achievement was efficiently predicted by the gene expression patterns, with an overall accuracy exceeding 90%. Finally, a negative predictive value of 100% was validated in an independent series, thus representing the first molecular predictor for clinical response to a specific combination drug treatment for AML. This trial has been registered at the European Medicines Agency and on the European Clinical Trials Database (https//www.clinicaltrialsregister.eu) as #2012-000334-19.The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-driven coronavirus disease 2019 (COVID-19) has caused unprecedented human death and has seriously threatened the global economy. click here Early data suggest a surge in proinflammatory cytokines in patients with severe COVID-19, which has been associated with poor outcomes. We recently postulated that the inflammatory response in patients with severe COVID-19 disease is not inhibited by natural killer (NK) cells, resulting in a “cytokine storm.” Here, we assessed the NK-cell functional activity and the associated cytokines and soluble mediators in hospitalized COVID-19 patients. Significantly impaired NK-cell counts and cytolytic activity were observed in COVID-19 patients when compared with healthy controls. Also, cytokines like interleukin 12 (IL12), IL15, and IL21 that are important for NK-cell activity were not detected systematically. Serum concentrations of soluble CD25 (sCD25)/soluble IL2 receptor α (sIL2-Rα) were significantly elevated and were inversely correlated with the percentage of NK cells. Impaired NK-cell cytolytic activity together with other laboratory trends including elevated sCD25 were consistent with a hyperinflammatory state in keeping with macrophage-activation syndrome. Our findings suggest that impaired counts and cytolytic activity of NK cells are important characteristics of severe COVID-19 and can potentially facilitate strategies for immunomodulatory therapies.

Accurate detection of brain metastasis (BM) is important for cancer patients. We aimed to systematically review the performance and quality of machine-learning-based BM detection on MRI in the relevant literature.

A systematic literature search was performed for relevant studies reported before April 27, 2020. We assessed the quality of the studies using modified tailored questionnaires of the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) criteria and the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). Pooled detectability was calculated using an inverse-variance weighting model.

A total of 12 studies were included, which showed a clear transition from classical machine learning (cML) to deep learning (DL) after 2018. The studies on DL used a larger sample size than those on cML. The cML and DL groups also differed in the composition of the dataset, and technical details such as data augmentation. The pooled proportions of detectability of BM were 88.7% (95% CI, 84-93%) and 90.