RESUMO
It is widely known that mold is one of important indices in assessing the quality of stored wheat. First, mold will decrease the quality of wheat kernels; the wheat kernels infected by mold can produce secondary metabolites, such as aflatoxins, ochratoxin A, zearalenone, fumonisins and so on. Second, the mycotoxins metabolized by mycetes are extremely harmful to humans; once the food or feed is made of by those wheat kernels infected by mold, it will cause serious health problems on human beings as well as animals. Therefore, the effective and accurate detection of wheat mold is vitally important to evaluate the storage and subsequent processing quality of wheat kernels. However, traditional methods for detecting wheat mold mainly rely on biochemical methods, which always involve complex and long pretreatment processes, and waste part of wheat samples for each detection. In view of this, this paper proposes a type of eco-friendly and nondestructive wheat mold detection method based on ultra weak luminescence. The specific implementation process is as follows: firstly, ultra weak luminescence signals of the healthy and the moldy wheat subsamples are measured by a photon analyzer; secondly, the approximate entropy and multiscale approximate entropy are introduced as the main classification features separately; finally, the detection model has been established based on the support vector machine in order to classify two types of wheat subsamples. The receiver operating characteristic curve of the newly established detection model shows that the highest classification accuracy rate can reach 93.1%, which illustrates that our proposed detection model is feasible and promising for detecting wheat mold.
Assuntos
Aflatoxinas , Micotoxinas , Zearalenona , Aflatoxinas/análise , Animais , Contaminação de Alimentos/análise , Fungos , Luminescência , Micotoxinas/análise , Triticum , Zearalenona/análiseRESUMO
OBJECTIVE@#To evaluate the performance of 3.0T magnetic resonance imaging examination (MRI) for the local detecting of muscle invasive bladder cancer following transurethral resection of bladder tumor (TURBT).@*METHODS@#Retrospective study identified 55 patients with pathology-proven bladder cancer who underwent transurethral resection of bladder tumor followed by 3.0T magnetic resonance imaging between September 2012 and April 2019 in our hospital. Two radiologists reviewed pelvic magnetic resonance imaging together and judged muscle invasive bladder cancer. Sensitivity, specificity and accuracy were calculated for the presence of muscle invasion by T2 weighted imaging (T2WI) only, diffusion-weighted imaging (DWI) only and T2WI+DWI compared with the findings at radical cystectomy as the reference standard.@*RESULTS@#Of the 55 patients with pathological results from radical cystectomy, 3.64% (2/55) had no residual disease; 29.09% (16/55) were non-muscle invasive bladder cancer on pathology, including 13 cases in T1 and 3 cases in Ta; 34.55% (19/55) were in stage T2 depending on pathology, 25.45% (14/55) in T3, and 7.27% (4/55) in T4. The average age was 60.76 years, ranging from 42 to 82 years. There were 48 males and 7 females in our study. Before pelvic MRI examination, all the patients received transurethral resection of bladder tumor, including 16 cases taking the operation in our hospital and 39 cases in other hospitals. The interval between the pelvic MRI examination and transurethral resection of bladder tumor was more than 2 weeks in all the patients. They all underwent radical cystectomy within 1 month after the pelvic MRI examination, and no patient underwent radiotherapy or chemotherapy in our study during the interval between the MRI examination and radical cystectomy. T2WI only, DWI only, and T2WI+DWI of 3.0T magnetic resonance imaging for readers were with sensitivity: 94.59%, 83.78%, 91.89%; with specificity: 66.67%, 77.78%, 72.22% and with accuracy: 85.45%, 81.82%, 85.45%, respectively.@*CONCLUSION@#3.0T MRI may have a role in diagnosing muscle invasive bladder cancer following TURBT. T2WI has the advantage of detecting the location of bladder tumor, and DWI has the advantage of differentiating between the benign and malignant lesion. 3.0T MRI T2WI+DWI has a good utility in the detection of muscle invasive bladder cancer following TURBT with satisfied accuracy.