Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.
Methicillin-resistant Staphylococcus aureus (MRSA) is a major multidrug-resistant bacterial pathogen. The evolution of MRSA is dynamic posing an ongoing threat to humans. The evolution of MRSA includes horizontal gene transfer, which is mediated by mobile genetic elements, plasmids, and bacteriophages, and also mutations. In this review, we clarify the recent trends in MRSA from the perspectives of drug-resistance transfer and uncontrollable infections, particularly those occurring in community settings. We first address the role of MRSA as a disseminator of multidrug resistance. We have studied the cell-to-cell transfer of drug resistance, in which transfer frequencies range from 10-3 to 10-8. The mechanisms of drug-resistance transfers include the self-transmission of large plasmids, the mobilization of small nonconjugative plasmids, the generalized transduction of phages, and the transfer of transposons with circular intermediates. We then discuss uncontrollable infections. Although several anti-MRSA agents have been developed, uncontrollable cases of MRSA infections are still reported. Examples include a case of uncontrollable sepsis arising from a community-associated MRSA (CA-MRSA) with the ST8/SCCmecIVl genotype, and a relapsing severe invasive infection of ST30/SCCmecIVc CA-MRSA in a student athlete. Some of these cases may be attributable to unique adhesins, superantigens, or cytolytic activities. The delayed diagnosis of highly adhesive and toxic infections in community settings may result in CA-MRSA diseases that are difficult to treat. Repeated relapse, persistent bacteremia, and infections of small-colony variants may occur. To treat MRSA infections in community settings, these unique features of MRSA must be considered to ensure that diagnostic delay is avoided.
Multi-walled carbon nanotubes/Mg-doped ZnO (MWNTs/Zn1-xMgxO) nanohybrids were prepared by co-precipitation method, and their photocatalytic activity for methyl orange (MO) was studied. Experimental results showed that Mg-doped ZnO nanoparticles were successfully deposited on the surface of MWNTs under annealing at 450 °C and 550 °C. The resultant MWNTs/Zn0.9Mg0.1O nanohybrids had better photocatalytic activity for degradation of methyl orange than pure ZnO: the rates of MO photodegradation were 100 % and 30 % for 1 h, respectively. The enhancement in the photocatalytic activity was attributed to the excellent electronic properties of MWNTs and Mg-doping.