Persistence and viable but non-culturable state induced by streptomycin in Erwinia amylovora

Persister cell and viable but non-culturable (VBNC) state of bacteria are survival strategies against antibiotics and various environmental stresses, respectively, but they tend to be ignored in agriculture fields, even though bacteria can regain their abilities to survive and produce disease once those stresses disappear. This study was carried out to determine whether persister cell and VBNC state in Erwinia amylovora are present after exposures to streptomycin, the length of their persistence, and the steps needed to decrease the inoculum. Persister cells were observed using biphasic killed growth curve for 4–8 h when the late stationary phase cells of E. amylovora were cultured in liquid medium containing streptomycin. This state was maintained for up to 12 h based on the colony forming units (CFUs) of the colonies that grew on the mannitol glutamate yeast extract (MGY) medium after streptomycin was removed. The CFUs on the MGY medium were lower than the total count determined using the LIVE/DEAD Kit, suggesting that persister cells and VBNC state might co-exist for up to 12 h after exposure to streptomycin. However, after 12 h, E. amylovora cells did not continue to grow on the medium for 9 days, suggesting that they entered a VBNC state at that time and remained in a persistent state. In addition, based on the Redox Sensor Green staining method, the presence of both states was confirmed for up to 12 h, and only then did the VBNC state became apparent. Furthermore, persister cells were observed for up to 24 h, and damaged cells reduced when E. amylovora cells were culture in distilled water with streptomycin, indicating that the uptake of lower nutrients in E. amylovora led to prolonged persister cells and VBNC state, which are more likely to survive after streptomycin treatments. The addition of sucrose and oxytetracycline to distilled water containing streptomycin reduced persister cells than other sources did. Thus, to inhibit the spread of fire blight, management techniques must consider the hazards of using streptomycin treatments that induce dormancy, such as persister cells and VBNC state, beyond the development of resistant strain

Association between shift work and obesity among female nurses: Korean Nurses’ Survey

Background: Shift work has been hypothesized as a risk factor for obesity. In this study, we investigated the association between current shift work and body mass index (BMI) among female nurses in Korea. The relationship between duration of shift work and BMI of the participants was also evaluated. Methods: This cross-sectional survey evaluated participants in the Korean Nurses’ Survey, conducted from October to December 2011, using web-based self-administered questionnaires. A total of 9,989 nurses were included among 10,000 who registered on the survey web site (5,287 shift workers and 4,702 non-shift workers). Current shift workers were divided into tertiles of shift work duration (0.08–3.00 years, n = 1,732; 3.08–6.75 years, n = 1,731; and 6.83–38.00 years, n = 1,686). The BMI thresholds of overweight and obesity were ≥23 kg/m2 and ≥25 kg/m2, respectively. Data were analyzed using SPSS software. Results: Mean participant age was 33.2 ± 8.6 years and the mean BMI was 20.9 ± 2.5 kg/m2. There were statistically significant differences in current smoking status, regular drinking habit, dietary habits, regular exercise, sleep problems and self-perceived health status according to duration of shift work. The overall prevalence of overweight/obesity (18.6%) and obesity (7.4%) increased significantly as shift work duration increased from the lowest to highest tertile (P for trend <0.001). Multivariate logistic regression analysis revealed no association between current shift work and BMI. However, after adjusting for potential confounders, the participants with the longest duration of shift work were 1.63 (95% CI, 1.22–2.17) times more likely to be overweight or obese than those with the shortest duration. There was a significant positive association between obesity and shift work duration in the unadjusted analysis; however, it was attenuated and no longer significant in the multivariate model. Conclusions: The duration of shift work was positively associated with prevalence of overweight/obesity in nurses in Korea. Although these findings need to be confirmed in prospective studies, they suggest that special attention should be paid to female nurses with a long duration of shift work

Polyelectrolyte complex micelles by self-assembly of polypeptide-based triblock copolymer for doxorubicin delivery

AbstractPolyelectrolyte complex micelles were prepared by self-assembly of polypeptide-based triblock copolymer as a new drug carrier for cancer chemotherapy. The triblock copolymer, poly(l-aspartic acid)-b-poly(ethylene glycol)-b-poly(l-aspartic acid) (PLD-b-PEG-b-PLD), spontaneously self-assembled with doxorubicin (DOX) via electrostatic interactions to form spherical micelles with a particle size of 60–80 nm (triblock ionomer complexes micelles, TBIC micelles). These micelles exhibited a high loading capacity of 70% (w/w) at a drug/polymer ratio of 0.5 at pH 7.0. They showed pH-responsive release patterns, with higher release at acidic pH than at physiological pH. Furthermore, DOX-loaded TBIC micelles exerted less cytotoxicity than free DOX in the A-549 human lung cancer cell line. Confocal microscopy in A-549 cells indicated that DOX-loaded TBIC micelles were transported into lysosomes via endocytosis. These micelles possessed favorable pharmacokinetic characteristics and showed sustained DOX release in rats. Overall, these findings indicate that PLD-b-PEG-b-PLD polypeptide micelles are a promising approach for anti-cancer drug delivery

Prediction of Cancer Patient Outcomes Based on Artificial Intelligence

Knowledge-based outcome predictions are common before radiotherapy. Because there are various treatment techniques, numerous factors must be considered in predicting cancer patient outcomes. As expectations surrounding personalized radiotherapy using complex data have increased, studies on outcome predictions using artificial intelligence have also increased. Representative artificial intelligence techniques used to predict the outcomes of cancer patients in the field of radiation oncology include collecting and processing big data, text mining of clinical literature, and machine learning for implementing prediction models. Here, methods of data preparation and model construction to predict rates of survival and toxicity using artificial intelligence are described

Effect of 5-aminolevulinic acid-based photodynamic therapy via reactive oxygen species in human cholangiocarcinoma cells

Cancer cells have been reported to exhibit an enhanced capacity for protoporphyrin IX (PpIX) synthesis facilitated by the administration of 5-aminolevulinic acid (ALA). We investigated the effect of ALA-based photodynamic therapy (PDT) on human cholangiocarcinoma cells (HuCC-T1). Since protoporphyrin IX (PpIX), a metabolite of ALA, can produce reactive oxygen species (ROS) under irradiation and then induce phototoxicity, ALA-based PDT is a promising candidate for the treatment of cholangiocarcinoma. When various concentrations of ALA (0.05–2 mM) were used to treat HuCC-T1 cells for 6 or 24 hours, the intracellular PpIX level increased according to the ALA concentration and treatment time. Furthermore, an increased amount of PpIX in HuCC-T1 cells induced increased production of ROS by irradiation, resulting in increased phototoxicity