texture
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127 s. : il.
svazky : ilustrace
- MeSH
- analýza potravin MeSH
- reologie MeSH
- stabilita léku MeSH
- Publikační typ
- periodika MeSH
- Konspekt
- Potravinářský průmysl
- NLK Obory
- nutriční terapie, dietoterapie a výživa
- fyziologie
We developed a swing arm device for acoustic measurement of food texture, which resolved difficulties of food texture evaluation. The device has a structure of balance-style and a probe in the device is moved downward along with motion of swing arm according to the balance of weights at both ends of the swing arm. The probe was inserted into a food sample. The device measured displacement and acceleration of the probe on food fracture by probe insertion with high precision until the probe stops inserting into a food sample. Using the displacement and acceleration of the probe on fracture, we calculated three parameters to determine food texture. Energy texture index (ETI) which is probe kinetic energy of acoustic vibration was evaluated by the vibration on food fracture. Audible energy texture index (aETI) could be introduced as food texture perceived by human sense of hearing, which was obtained by multiplying ETI by human hearing sensitivity. It was found that the ETI and aETI can be used for measurement of characteristic food texture detected at a tooth and perceived in brain, respectively. Food friction index (FFI) to explain the friction strength of a probe against a food sample was theoretically formulated under the condition of probe motion in the device. FFI was found to be useful not only for crispy food like biscuit but for soft food. The measured FFI indicated characteristic of smoothness of probe insertion into food sample. PRACTICAL APPLICATIONS: The swing arm device can be used to estimate food texture by measuring probe vibration energy on food fracture. Energy texture index (ETI) and Audible energy texture index (aETI) are introduced into measurements of food with crispness which emits sounds on fracture by probe insertion. ETI is an index to estimate probe vibration energy, while aETI is one to estimate food texture by human sense of hearing that was corrected by human hearing sensitivity as human hearing sensitivity is highest around sound frequency ranging from 1,000 to 4,000 Hz. Food friction index (FFI) was also obtained by the device to evaluate smoothness of probe insertion into a food sample. ETI, aETI, and FFI can be useful parameters for food texture of water melon, pear, persimmon, apple, cookie, potato chips, and biscuit. FFI is especially suitable for evaluation of soft food such as banana, avocado, mango, melon, peach, pudding, or bread.
- MeSH
- akustika * MeSH
- analýza potravin přístrojové vybavení metody MeSH
- design vybavení MeSH
- kinetika MeSH
- lidé MeSH
- manipulace s potravinami přístrojové vybavení metody MeSH
- sluchové testy MeSH
- teoretické modely MeSH
- vibrace MeSH
- zrychlení MeSH
- zvuk MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Texture analysis as a versatile tool for testing the inner structure of materials have been widely used. Though being also used in pharmaceutical industry, it has not been included in standard procedures for evaluation of drug dosage forms. The aim of this study is to measure the thickness of gel layer using texture analysis for the prediction of dissolution profile of very soluble drugs based on hydrophilic and hydrophilic-lipophilic matrix tablets. For the evaluation of the correlation between the thickness of the gel layer as an independent variable and the amount of a released drug as a dependent variable at given time intervals, the multivariate method of partial least squares – PLS-2 regression was used. For the prediction of dissolution characteristics of matrix tablets, a PLS-2 model validated by full cross-validation was developed. A PLS-2 model validated by full cross-validation was developed.
PURPOSE: Imaging biomarker research focuses on discovering relationships between radiological features and histological findings. In glioblastoma patients, methylation of the O(6)-methylguanine methyltransferase (MGMT) gene promoter is positively correlated with an increased effectiveness of current standard of care. In this paper, the authors investigate texture features as potential imaging biomarkers for capturing the MGMT methylation status of glioblastoma multiforme (GBM) tumors when combined with supervised classification schemes. METHODS: A retrospective study of 155 GBM patients with known MGMT methylation status was conducted. Co-occurrence and run length texture features were calculated, and both support vector machines (SVMs) and random forest classifiers were used to predict MGMT methylation status. RESULTS: The best classification system (an SVM-based classifier) had a maximum area under the receiver-operating characteristic (ROC) curve of 0.85 (95% CI: 0.78-0.91) using four texture features (correlation, energy, entropy, and local intensity) originating from the T2-weighted images, yielding at the optimal threshold of the ROC curve, a sensitivity of 0.803 and a specificity of 0.813. CONCLUSIONS: Results show that supervised machine learning of MRI texture features can predict MGMT methylation status in preoperative GBM tumors, thus providing a new noninvasive imaging biomarker.
- MeSH
- DNA modifikační methylasy genetika MeSH
- enzymy opravy DNA genetika MeSH
- glioblastom diagnostické zobrazování genetika chirurgie MeSH
- lidé MeSH
- magnetická rezonanční tomografie metody MeSH
- metylace DNA * MeSH
- mozek diagnostické zobrazování chirurgie MeSH
- nádorové biomarkery genetika MeSH
- nádorové supresorové proteiny genetika MeSH
- nádory mozku diagnostické zobrazování genetika chirurgie MeSH
- promotorové oblasti (genetika) MeSH
- retrospektivní studie MeSH
- ROC křivka MeSH
- support vector machine MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
