Adhesion of microbes using 3‐aminopropyl triethoxy silane and specimen stabilisation techniques for analytical transmission electron microscopy

Abstract

SummaryA variety of adhesive support-®lms were tested for their ability to adhere various biological specimens for transmission electron microscopy. Support ®lms primed with 3-amino-propyl triethoxy silane (APTES), poly-L-lysine, carbon and ultraviolet-B (UV-B)-irradiated carbon were tested for their ability to adhere a variety of biological specimens including axenic cultures of Bacillus subtilis and Escherichia coli and wild-type magnetotactic bacteria. The effects of UV-B irradiation on the support ®lm in the presence of air and electrostatic charge on primer deposition were tested and the stability of adhered specimens on various surfaces was also compared. APTES-primed UV-Birradiated Pioloform TM was consistently the best adhesive, especially for large cells, and when adhered specimens were UV-B irradiated they became remarkably stable under an electron beam. This assisted the acquisition of in situ phase-contrast lattice images from a variety of biominerals in magnetotactic bacteria, in particular metastable greigite magnetosomes. Washing tests indicated that specimens adhering to APTES-primed UV-B-irradiated Pioloform TM were covalently coupled. The electron beam stability was hypothesised to be the result of mechanical strengthening of the specimen and support ®lm and the reduced electrical resistance in the specimen and support ®lm due to their polymerization and covalent coupling.

A descriptive study of mastitis in Australian breastfeeding women: incidence and determinants

“…These univariate level tests were undertaken using logistic regression. Variables were entered in the model if the p-value of the Wald statistic was = 0.2 [16]. These included group (ABFAB, FBC or FPH), education, income (stratified in three levels), cracked nipple and duration of pain.…”

“…Variables were eliminated one at a time using logistic regression, only those with a p-value of the Wald statistic of = 0.05 were retained [16]. The process was repeated until only significant variables remained.…”

“…At this stage all variables eliminated in the original univariate analysis were added back into the model one at a time to check that none had become significant given the reduced model. The only continuous variable, "duration of pain" was then checked for the correct parametric form using fractional polynomials [16]. The duration of pain was found to be non-linear and was dichotomised into pain in two levels (<four weeks and pain lasting four weeks or more).…”

“…The sensitivity of the model, that is, how often it correctly predicted the outcome (y) given the value of a covariate (x) was tested using the area under the ROC curve. To be said to have good discrimination, a model should have a statistical value of ≥ 0.7 from the ROC test, that is the area under the ROC curve should be large so that for every increase in specificity you move closer to a high sensitivity [16]. The lroc test identified that the area under the ROC curve was 0.6195.…”

Effects of risk-based multifactorial fall prevention on health-related quality of life among the community-dwelling aged: a randomized controlled trial

“…In the analysis of HRQOL outcome variables, the baseline differences between the groups were assessed using logistic regression. During the follow-up, the changes in HRQOL items were examined by logistic regression analyses with generalised estimation equations (GEE) to account for correlations between repeated measurements [27]. Cumulative logistic models were used for ordinal dependent items consisting of three categories and binary logistic models for dependent items having two categories.…”