ABSTRACT
Myelodysplastic syndromes (MDS) are common malignant disorders with a poor prognosis. It is necessary to search for new rapid diagnostic methods to detect MDS patients with cytogenetic changes. The aim of the study was to assess new hematological neutrophil- and monocyte- related parameters I then bone marrow of MDS patient with and without cytogenetic changes. A total of 45 patients with MDS, including 17 patients with cytogenetic changes, were examined. The study was conducted using the Sysmex XN-Series hematological analyzer. New neutrophil and monocyte parameters, such as immature granulocytes (IG), neutrophil reactivity intensity (NEUT-RI), neutrophil granularity intensity (NEUT-GI), neutrophil size (NE-FSC) and neutrophil/monocyte data relating to granularity, activity and volume (NE-WX/MO-WX, NE-WY/MO-WY, NE-WZ/MO-WZ, MO-X, MO-Y, MO-Z) were evaluated. We observed higher median proportions of NE-WX, NE-WY, NE-WZ, and IG counts in MDS patients with cytogenetic changes than in patients without cytogenetic changes. The NE-FSC parameter was lower in MDS patients with cytogenetic changes than in patients without cytogenetic changes. The combination of new neutrophil parameters was found to be a new successful approach in distinguishing MDS patients with cytogenetic changes from patients without cytogenetic changes. It appears that there may be unique neutrophil parameter signatures associated with an underlying mutation.
ABSTRACT
Remote sensing (RS) is currently regarded as one of the standard tools used for mapping invasive and expansive plants for scientific purposes and it is increasingly widely used in nature conservation management. The applicability of RS methods is determined by its limitations and requirements. One of the most important limitations is the species percentage cover at which the classification result is correct and useful for nature conservation. The primary objective, carried out in 2017 in three areas of Poland, was to determine the minimum percentage cover from which it is possible to identify a target species by RS methods. A secondary objective of this research, related to the requirements of the method, was to optimize the set of training polygons for a target species in terms of the number of polygons and abundance percentage cover of the target species. Our method has to be easy to use, effective, and applicable, therefore the analysis was carried out using the basic set of rasters-the first 30 channels after the Minimum Noise Fraction (MNF) transformation (the mosaic of hyperspectral data from HySpex sensors with spectral range 0.4-2.5 µm) and commonly used Random Forest algorithm. The analysis used airborne hyperspectral data with a spatial resolution of 1 m to perform classification of one invasive and three expansive plants-two grasses and two large perennials. On-ground training and validation data sets were collected simultaneously with airborne data collection. When testing different classification scenarios, only the set of training polygons for a target species was changed. Classification results were evaluated based on three methods: accuracy measures (Kappa and F1), true-positive pixels in subclasses with different species cover and compatibility with field mapping. The classification results indicate that to classify the target plant species at the accepted level, the training dataset should contain polygons with a species cover ranging from 80-100%. Training performed only using polygons with a species characterized by a variable, but lower, cover (20-70%) and missing samples in the 80-100% range, led to a map which was not acceptable because of a high overestimation of target species. We achieved effective identification of species in areas where the species cover is above 50%, considering that ecosystems are heterogeneous. The results of these studies developed a methodology of field data acquisition and the necessity of synchronization in the acquisition of airborne data, and training and validation of on-ground sampling.
ABSTRACT
INTRODUCTION: Lung cancer is the most common cause of cancer-related death worldwide, killing almost 22,000 people in Poland every year. Low-dose computed tomography (LDCT) is the most promising tool of secondary prophylaxis leading to early detection and thus successful treatment of this malignancy. Knowledge about socio-demographic factors that affect participation in lung cancer early detection programs is essential for the future design and implementation of such programs. MATERIAL AND METHODS: Among the 8649 participants of the Pomeranian Lung Cancer Screening Program (PLCSP), 1619 individuals responded to a questionnaire that had been designed to assess socio-demographic data of participants at high risk of developing lung cancer. The survey was conducted on-site after reception of results by the program participants. RESULTS: Among the survey participants, 777 (48%) were current cigarette smokers. The majority of them represented low or medium level of wealth status. The respondents positively evaluated the promotional campaign during the PLCSP, although 43% of them indicated family and friends as a source of information about the program. As the most important action that stimulated the participation, 46% of the respondents indicated the awareness campaign involving a celebrity, and 45% of them indicated the presence of cancer in the family. The influence of healthcare employees on the participation in the screening program was minimal. More than half of the respondents (53%) declared a willingness to co-finance a similar prophylactic program in the future in an amount not exceeding 100 PLN. CONCLUSIONS: An effective promotional campaign in the media, the influence of family and a campaign involving a celebrity promoted attendance at the screening program. The influence of healthcare employees on the participation in the program was minimal. The majority of the screened population declared a willingness to actively participate in the costs of LDCT examination.
