The role of MR tractography in pre-surgical planning: Personal series of 25 cases and a review of the literature

Diffusion tensor imaging (DTI) contains a wealth of information on molecular diffusion in biological tissues [1,2]. Visualizing the white-matter tracts using diffusion anisotropy maps represents one of the applications with a major impact on neurosurgical case management [3]. Knowledge of the topography, integrity, and involvement by the pathological process of the white matter tracts is an important factor in pre-surgical planning for patients with brain lesions. We have evaluated the clinical utility of a magnetic resonance tractography technique based on DTI. We studied, in a prospective manner, 25 cases with lesions involving salient intracerebral and medullary tumors (22 and 3 cases respectively). All cases followed a preoperative imaging protocol that included DTI on top of the usual MR imaging protocol. We analyzed the DTI findings preoperatively and looked at the significant information that influences the surgical plan: position of the significant white matter tracts, the degree of their involvement in the pathological process and anatomical integrity, relationships with important anatomical landmarks and with the major surgical approach paths. We present the postoperative results and some of the most illustrative cases in the series and compare our results with the similar studies in the literature. Our experience, based on the results of the present study strongly suggests that in depth knowledge of the white matter tracts involvement in an intracerebral or intramedullary pathological process improves significantly the surgical planning in terms of surgical procedure safety and functional outcome

In Situ Hyperspectral Remote Sensing for Monitoring of Alpine Trampled and Recultivated Species

Vegetation, through its condition, reflects the properties of the environment. Heterogeneous alpine ecosystems play a critical role in global monitoring systems, but due to low accessibility, cloudy conditions, and short vegetation periods, standard monitoring methods cannot be applied comprehensively. Hyperspectral tools offer a variety of methods based on narrow-band data, but before extrapolation to an airborne or satellite scale, they must be verified using plant biometrical variables. This study aims to assess the condition of alpine sward dominant species (Agrostis rupestris, Festuca picta, and Luzula alpino-pilosa) of the UNESCO Man&Biosphere Tatra National Park (TPN) where the high mountain grasslands are strongly influenced by tourists. Data were analyzed for trampled, reference, and recultivated polygons. The field-obtained hyperspectral properties were verified using ground measured photosynthetically active radiation, chlorophyll content, fluorescence, and evapotranspiration. Statistically significant changes in terms of cellular structures, chlorophyll, and water content in the canopy were detected. Lower values for the remote sensing indices were observed for trampled plants (about 10−15%). Species in recultivated areas were characterized by a similar, or sometimes improved, spectral properties than the reference polygons; confirmed by fluorescence measurements (Fv/Fm). Overall, the fluorescence analysis and remote sensing tools confirmed the suitability of such methods for monitoring species in remote mountain areas, and the general condition of these grasslands was determined as good

Assessment of the Antioxidant Activity and Quality Attributes of Yogurt Enhanced with Wild Herbs Extracts

The milk and yogurt products assortment has expanded by their enhancement with herb extracts, fibres extracted from by-products of the fruit processing industry and also fresh spices. The aim of the present study was to test to what extent the addition of different herb extracts in yogurt will improve its qualitative characteristics and antioxidant activity. The aqueous extracts obtained from the four plants are considered in this study, respectively, thistle (Silybum marianum L.), hawthorn (Crataegus monogyna), sage (Salvia officinalis L.), and marjoram (Origanum vulgare L.). It was examined the effect of aqueous extracts prepared from four herbs (0.25/1%) (w/w) on yogurt’s qualitative characteristics (pH, titratable acidity, syneresis, water holding capacity, antioxidant activity, colour parameters, and rheological parameters) on both one day and 28 days after preparation. The final results show that the physicochemical and rheological properties of the yoghurt with herb extracts addition were improved compared to the control sample after 28 days of storage. The best results in terms of antioxidant properties were obtained when marjoram extract (Origanum vulgare L.) was incorporated. According to the data obtained, the best quality in terms of the physicochemical and rheological properties were in the case of the sample with 0.5% thistle extract (Silybum marianum L.) addition, while from point of view of the nutritional value, the best quality was in the case of the sample with 1% marjoram extract (Origanum vulgare L.) addition. The present study leads to the conclusion that yogurts enhanced with natural extracts may serve as functional food products, with significant health benefits

Comparison of Random Forest, Support Vector Machines, and Neural Networks for Post-Disaster Forest Species Mapping of the Krkonoše/Karkonosze Transboundary Biosphere Reserve

Mountain forests are exposed to extreme conditions (e.g., strong winds and intense solar radiation) and various types of damage by insects such as bark beetles, which makes them very sensitive to climatic changes. Therefore, continuous monitoring is crucial, and remote-sensing techniques allow the monitoring of transboundary areas where a common policy is needed to protect and monitor the environment. In this study, we used Sentinel-2 and Landsat 8 open data to assess the forest stands classification of the UNESCO Krkonoše/Karkonosze Transboundary Biosphere Reserve, which is undergoing dynamic changes in recovering woodland vegetation due to an ecological disaster that led to damage and death of a large portion of the forests. Currently, in this protected area, dry big trunks and branches coexist with naturally occurring young forests. This heterogeneity generates mixes, which hinders the automation of classification. Thus, we used three machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN)—to classify dominant tree species (birch, beech, larch and spruce). The best results were obtained for the SVM RBF classifier, which offered an average median F1-score that oscillated around 67.2–91.5% depending on the species. The obtained maps, which were based on multispectral satellite images, were also compared with classifications made for the same area on the basis of hyperspectral APEX imagery (288 spectral bands with three-meter resolution), indicating high convergence in the recognition of woody species

EFFECTS OF SOME VEGETABLE PROTEINS ADDITION ON YOGURT QUALITY

Yogurt is the most famous fermented milk product, with yogurt consumption having grown over the years and is still rising in many countries. The aim of this study was to determine the effects of different vegetable proteins on the rheological, physicochemical and sensorial properties of yogurt with 10 % fat. The studied vegetable proteins were pea protein, soya protein, wheat gluten, hemp protein and pumpkin seed flour. The amount of vegetable protein added to the raw milk before pasteurization was calculated so that the yogurt contained 4 % of the protein. The finished product is a functional food that uses no preservatives, additives or genetically modified organisms. The addition of vegetable proteins in the yogurt formulation modified their rheological, physicochemical and sensory properties. It is possible to produce yogurts containing vegetable proteins without changing the technological procedure and with a good quality for the consumers

Cardiac masses and the role of imaging in their diagnostic

Myxomas are the most common primary tumors of the adult heart and should be considered in the differential diagnosis of intracavitary cardiac masses, along with thrombi and vegetations

Comparison of Support Vector Machines and Random Forests for Corine Land Cover Mapping

Land cover information is essential in European Union spatial management, particularly that of invasive species, natural habitats, urbanization, and deforestation; therefore, the need for accurate and objective data and tools is critical. For this purpose, the European Union’s flagship program, the Corine Land Cover (CLC), was created. Intensive works are currently being carried out to prepare a new version of CLC+ by 2024. The geographical, climatic, and economic diversity of the European Union raises the challenge to verify various test areas’ methods and algorithms. Based on the Corine program’s precise guidelines, Sentinel-2 and Landsat 8 satellite images were tested to assess classification accuracy and regional and spatial development in three varied areas of Catalonia, Poland, and Romania. The method is dependent on two machine learning algorithms, Random Forest (RF) and Support Vector Machine (SVM). The bias of classifications was reduced using an iterative of randomized training, test, and verification pixels. The ease of the implementation of the used algorithms makes reproducing the results possible and comparable. The results show that an SVM with a radial kernel is the best classifier, followed by RF. The high accuracy classes that can be updated and classes that should be redefined are specified. The methodology’s potential can be used by developers of CLC+ products as a guideline for algorithms, sensors, and the possibilities and difficulties of classifying different CLC classes

Microvesicles and Microvesicle-Associated microRNAs Reflect Glioblastoma Regression: Microvesicle-Associated miR-625-5p Has Biomarker Potential

Glioblastoma (GB) is the most aggressive and recurrent form of brain cancer in adults. We hypothesized that the identification of biomarkers such as certain microRNAs (miRNAs) and the circulating microvesicles (MVs) that transport them could be key to establishing GB progression, recurrence and therapeutic response. For this purpose, circulating MVs were isolated from the plasma of GB patients (before and after surgery) and of healthy subjects and characterized by flow cytometry. OpenArray profiling and the individual quantification of selected miRNAs in plasma and MVs was performed, followed by target genes’ prediction and in silico survival analysis. It was found that MVs’ parameters (number, EGFRvIII and EpCAM) decreased after the surgical resection of GB tumors, but the inter-patient variability was high. The expression of miR-106b-5p, miR-486-3p, miR-766-3p and miR-30d-5p in GB patients’ MVs was restored to control-like levels after surgery: miR-106b-5p, miR-486-3p and miR-766-3p were upregulated, while miR-30d-5p levels were downregulated after surgical resection. MiR-625-5p was only identified in MVs isolated from GB patients before surgery and was not detected in plasma. Target prediction and pathway analysis showed that the selected miRNAs regulate genes involved in cancer pathways, including glioma. In conclusion, miR-625-5p shows potential as a biomarker for GB regression or recurrence, but further in-depth studies are needed