Nondesulfurizing benzothiophene biotransformation to hetero and homodimeric ortho-substituted diaryl disulfides by the model PAH-degrading Sphingobium barthaii.

Understanding the biotransformation mechanisms of toxic sulfur-containing polycyclic aromatic hydrocarbon (PASH) pollutants such as benzothiophene (BT) is useful for predicting their environmental fates. In the natural environment, nondesulfurizing hydrocarbon-degrading bacteria are major active contributors to PASH biodegradation at petroleum-contaminated sites; however, BT biotransformation pathways by this group of bacteria are less explored when compared to desulfurizing organisms. When a model nondesulfurizing polycyclic aromatic hydrocarbon-degrading soil bacterium, Sphingobium barthaii KK22, was investigated for its ability to cometabolically biotransform BT by quantitative and qualitative methods, BT was depleted from culture media but was biotransformed into mostly high molar mass (HMM) hetero and homodimeric ortho-substituted diaryl disulfides (diaryl disulfanes). HMM diaryl disulfides have not been reported as biotransformation products of BT. Chemical structures were proposed for the diaryl disulfides by comprehensive mass spectrometry analyses of the chromatographically separated products and were supported by the identification of transient upstream BT biotransformation products, which included benzenethiols. Thiophenic acid products were also identified, and pathways that described BT biotransformation and novel HMM diaryl disulfide formation were constructed. This work shows that nondesulfurizing hydrocarbon-degrading organisms produce HMM diaryl disulfides from low molar mass polyaromatic sulfur heterocycles, and this may be taken into consideration when predicting the environmental fates of BT pollutants.

Validity and reliability of velocity measurements on ultrasonography using custom software with an optical-flow algorithm.

[Purpose] The purposes of this study were: 1) to validate a commercial software program using an optical-flow algorithm to measure the velocity of muscle movement; and 2) to determine optimal image quality and the size and location of regions of interest. [Materials and Methods] First, a block of pork thigh muscle was pulled at 33 different constant velocities. Subsequently, an accelerometer, a high-velocity camera, and ultrasonography were used to obtain measurements, and an Echolizer software was used to determine ultrasound-based velocities. Finally, the impact of the location and size of the regions of interest and the brightness and contrast of the images was analyzed. [Results] The regression equation was expressed as y=1.150 × -0.071 with a determination coefficient of 0.996. The average absolute error of the software was 0.02 mm/s, and the average relative error was 0.20% of the actual velocity between 2.5 and 16.5 mm/s after the regression equation was applied to the measured data. The accuracy of measurement was reduced owing to the increased size of the regions of interest, which included poor image quality or a deeper zone. [Conclusion] Our method of measuring muscle velocity using a custom program showed high validity and reliability. It is necessary to use the regression equation in the program to improve accuracy. However, the validity of the method could be reduced if the regions of interest involve deep tissues or areas with poor visualization of the muscle bundles, or if the brightness and contrast of the image are set inaccurately.