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BACKGROUND: We compared the BACTEC Peds Plus (Becton Dickinson, USA) and BacT/Alert PF (bioMerieux, France) pediatric blood culture bottles in the context of recovery and time to detection (TTD) of bacteria and fungi from pediatric patients. METHODS: Blood samples were collected for culture from pediatric patients who were hospitalized during 2010 at a university hospital. BACTEC Peds Plus and BacT/Alert PF bottles were placed in the BACTEC FX and BacT/Alert 3D blood culture system, respectively, and tested for 5 days. Bottles flagged by instruments as positive were removed from the instruments and the TTDs were recorded. RESULTS: A total of 5,018 sets (1 set, 1 BACTEC Peds Plus and 1 BacT/Alert PF) were evaluated. Overall, the recovery proportions for BACTEC Peds Plus and BacT/Alert PF bottles were 57% (134/195) and 69% (112/195), respectively. There was a significant difference between the 0.38% contamination rate in BacT/Alert PF bottles and the 0.16% contamination rate in BACTEC Peds Plus bottles (P=0.035). The average TTD for all microorganisms was significantly decreased for the BACTEC Peds Plus bottles (P=0.021), but was increased for Candida parapsilosis compared to the results for the BacT/Alert PF bottles (P=0.028). CONCLUSION: We conclude that the rate of detection and contamination is higher when BacT/Alert PF bottles are used than when BACTEC Peds Plus bottles are used for pediatric blood culture. The BACTEC Peds Plus bottles detect nearly all enrolled microorganisms significantly faster than do the BacT/Alert PF bottles.
Bacteria ; Candida ; Fungi ; Humans

Background: There are limited data on the accuracy of cloud-based speech recognition (SR) open application programming interfaces (APIs) for medical terminology. This study aimed to evaluate the medical term recognition accuracy of current available cloud-based SR open APIs in Korean. Methods: We analyzed the SR accuracy of currently available cloud-based SR open APIs using real doctor–patient conversation recordings collected from an outpatient clinic at a large tertiary medical center in Korea. For each original and SR transcription, we analyzed the accuracy rate of each cloud-based SR open API (i.e., the number of medical terms in the SR transcription per number of medical terms in the original transcription). Results: A total of 112 doctor–patient conversation recordings were converted with three cloud-based SR open APIs (Naver Clova SR from Naver Corporation; Google Speech-toText from Alphabet Inc.; and Amazon Transcribe from Amazon), and each transcription was compared. Naver Clova SR (75.1%) showed the highest accuracy with the recognition of medical terms compared to the other open APIs (Google Speech-to-Text, 50.9%, P < 0.001; Amazon Transcribe, 57.9%, P < 0.001), and Amazon Transcribe demonstrated higher recognition accuracy compared to Google Speech-to-Text (P< 0.001). In the sub-analysis, Naver Clova SR showed the highest accuracy in all areas according to word classes, but the accuracy of words longer than five characters showed no statistical differences (Naver Clova SR, 52.6%; Google Speech-to-Text, 56.3%; Amazon Transcribe, 36.6%). Conclusion Among three current cloud-based SR open APIs, Naver Clova SR which manufactured by Korean company showed highest accuracy of medical terms in Korean, compared to Google Speech-to-Text and Amazon Transcribe. Although limitations are existing in the recognition of medical terminology, there is a lot of rooms for improvement of this promising technology by combining strengths of each SR engines.

The anti-melanogenic activity of 259 actinomycete strains was tested, and based on the results for the inhibition of mushroom tyrosinase activity and the reduction in melanin content, Micromonospora sp. JCS1 and JCS7 were selected as the strains with the highest anti-melanogenic potential. The activity-guided fractionation of extracts from JCS1 and JCS7 led to the isolation of the dipeptides cyclo(L-Phenyl alanine (Phe)-L-Proline (Pro)) (1) and cyclo(L-Tryptophan (Trp)-L-Proline (Pro)) (2). These two compounds were tested for their inhibition of mushroom tyrosinase by monitoring L-DOPA levels and melanin production. Cyclo(L-Phe-L-Pro) (1) and cyclo(L-Trp-L-Pro) (2) were thus confirmed to have the potential for use in functional whitening cosmetics containing actinomycete-derived secondary metabolites.