Analysis of changes in fruit tissue after the pulsed electric field treatment using optical coherence tomography

The pulsed electric field (PEF) is one of the non-thermal methods used in the food industry for prolonging food preservation or obtaining better quality of end products. The structure of fruit and vegetable tissues subjected to PEF treatment changes under the influence of short-term high voltage electrical impulses. In this process, the hydrophilic spaces in the cell membranes occur. The authors present the results of the assessment of structural changes in fruit subjected to PEF, using the textural analysis of sub-peel layers. The images were obtained by optical coherence tomography (OCT) at an infrared wavelength of 1300 nm. The OCT cross-sections revealed the zone of strong infrared light reflection from internal structures indicating the loss of parenchymatic tissue integrity. The intensity of these changes depended on fruit type and used parameters of PEF. It was shown that the increasing intensity of the electric field affecting the tissue structure of raspberry or grape fruit generally increases the entropy, standard deviation and the mean of their OCT images. Changes in these feature values are usually not proportional to the field strength (0, 3.3, 5 kV/cm) and depend on the depth below the fruit surface. The raspberry fruit is more sensitive to PEF because at the strength of 5 kV/cm the corresponding features of grape fruit behave similarly with 10 times more field pulses. The OCT method can be used to assess noninvasively the suitability of fruit for further stages of processing, e.g. in PEF assisted pressing of fruit juice

Method of Biomass Discrimination for Fast Assessment of Calorific Value

Crop byproducts are alternatives to nonrenewable energy resources. Burning biomass results in lower emission of undesirable nitrogen and sulfur oxides and contributes no significant greenhouse effect. There is a diverse range of energy-useful biomass, including in terms of calorific value. This article presents a new method of discriminating biomass, and of determining its calorific value. The method involves extracting the selected texture features on the surface of a briquette from a microscopic image and then classifying them using supervised classification methods. The fractal dimension, local binary pattern (LBP), and Haralick features are computed and then classified by linear discrimination analysis (LDA). The discrimination results are compared with the results obtained by random forest (RF) and deep neural network (DNN) type classifiers. This approach is superior in terms of complexity and operating time to other methods such as, for instance, the calorimetric method or analysis of the chemical composition of elements in a sample. In the normal operation mode, our method identifies the calorific value in the time of about 100 s, i.e., 90 times faster than traditional combustion of material samples. In predicting from a single sample image, the overall average accuracy of 95% was achieved for all tested classifiers. The authors’ idea to use ten input images of the same material and then majority voting after classification increases the discrimination system accuracy above 99%

Concentration of Selected Adipokines and Factors Regulating Carbohydrate Metabolism in Patients with Head and Neck Cancer in Respect to Their Body Mass Index

Head and neck cancers (HNCs) are a group of tumors not common in European populations. So far, not much is known about the role of obesity, adipokines, glucose metabolism, and inflammation in the pathogenesis of HNC. The aim of the study was to determine the concentrations of ghrelin, omentin-1, adipsin, adiponectin, leptin, resistin, visfatin, glucagon, insulin, C-peptide, glucagon-like peptide-1 (GLP-1), plasminogen activator inhibitor-1 (PAI-1), and gastric inhibitory peptide (GIP) in the blood serum of HNC patients depending on their body mass index (BMI). The study included 46 patients divided into two groups according to their BMI values: the normal BMI group (nBMI) included 23 patients with BMI < 25 kg/m2 and the increased BMI group (iBMI) included patients with BMI ≥ 25 kg/m2. A control group (CG) included 23 healthy people (BMI < 25 kg/m2). Statistically significant differences in the levels of adipsin, ghrelin, glucagon, PAI-1, and visfatin were shown between nBMI and CG. In the case of nBMI and iBMI, statistically significant differences were observed in the concentrations of adiponectin, C-peptide, ghrelin, GLP-1, insulin, leptin, omentin-1, PAI-1, resistin, and visfatin. The obtained results indicate a disruption of endocrine function of adipose tissue and impaired glucose metabolism in HNC. Obesity, which is not a typical risk factor for HNC, may aggravate the negative metabolic changes associated with this type of neoplasm. Ghrelin, visfatin, PAI-1, adipsin, and glucagon might be related to head and neck carcinogenesis. They seem to be promising directions for further research

Concentration of Selected Adipokines and Factors Regulating Carbohydrate Metabolism in Patients with Head and Neck Cancer in Respect to Their Body Mass Index

Head and neck cancers (HNCs) are a group of tumors not common in European populations. So far, not much is known about the role of obesity, adipokines, glucose metabolism, and inflammation in the pathogenesis of HNC. The aim of the study was to determine the concentrations of ghrelin, omentin-1, adipsin, adiponectin, leptin, resistin, visfatin, glucagon, insulin, C-peptide, glucagon-like peptide-1 (GLP-1), plasminogen activator inhibitor-1 (PAI-1), and gastric inhibitory peptide (GIP) in the blood serum of HNC patients depending on their body mass index (BMI). The study included 46 patients divided into two groups according to their BMI values: the normal BMI group (nBMI) included 23 patients with BMI 2 and the increased BMI group (iBMI) included patients with BMI ≥ 25 kg/m2. A control group (CG) included 23 healthy people (BMI 2). Statistically significant differences in the levels of adipsin, ghrelin, glucagon, PAI-1, and visfatin were shown between nBMI and CG. In the case of nBMI and iBMI, statistically significant differences were observed in the concentrations of adiponectin, C-peptide, ghrelin, GLP-1, insulin, leptin, omentin-1, PAI-1, resistin, and visfatin. The obtained results indicate a disruption of endocrine function of adipose tissue and impaired glucose metabolism in HNC. Obesity, which is not a typical risk factor for HNC, may aggravate the negative metabolic changes associated with this type of neoplasm. Ghrelin, visfatin, PAI-1, adipsin, and glucagon might be related to head and neck carcinogenesis. They seem to be promising directions for further research