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Microscopic examination plays a significant role in the initial screening for a variety of hematological, as well as non-hematological, diagnoses. Microscopic blood smear examination that is considered a key diagnostic technique, is in recent clinical practice still performed manually, which is not only time consuming, but can lead to human errors. Although automated and semi-automated systems have been developed in recent years, their high purchasing and maintenance costs make them unaffordable for many medical institutions. Even though much research has been conducted lately to explore more accurate and feasible solutions, most researchers had to deal with a lack of medical data. To address the lack of large-scale databases in this field, we created a high-resolution dataset containing a total of 16027 annotated white blood cells. Moreover, the dataset covers overall 9 types of white blood cells, including clinically significant pathological findings. Since we used high-quality acquisition equipment, the dataset provides one of the highest quality images of blood cells, achieving an approximate resolution of 42 pixels per 1 μm.
- MeSH
- leukocyty * cytologie patologie MeSH
- lidé MeSH
- mikroskopie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- dataset MeSH
- práce podpořená grantem MeSH
Listeria monocytogenes (Lm) is a ubiquitous bacterium that causes listeriosis, a serious foodborne illness. In the nature-to-human transmission route, Lm can prosper in various ecological niches. Soil and decaying organic matter are its primary reservoirs. Certain clonal complexes (CCs) are over-represented in food production and represent a challenge to food safety. To gain new understanding of Lm adaptation mechanisms in food, the genetic background of strains found in animals and environment should be investigated in comparison to that of food strains. Twenty-one partners, including food, environment, veterinary and public health laboratories, constructed a dataset of 1484 genomes originating from Lm strains collected in 19 European countries. This dataset encompasses a large number of CCs occurring worldwide, covers many diverse habitats and is balanced between ecological compartments and geographic regions. The dataset presented here will contribute to improve our understanding of Lm ecology and should aid in the surveillance of Lm. This dataset provides a basis for the discovery of the genetic traits underlying Lm adaptation to different ecological niches.
This article presents the dataset of the healthcare systems indicators of 120 countries during 2010-2017, which is related to the research article "Cross-efficiency evaluation in the presence of flexible measures with an application to healthcare systems" [1]. The data is collected from the World Bank and selected for the 120 countries. Depending on their role in the performance of the healthcare systems, the indicators are categorized into input (I), output (O) and flexible measure (FM) where the FM measure can play either role of input or output in the healthcare system. The dataset can be used to perform efficiency as well as cross-efficiency analysis of the healthcare systems using methods such as data envelopment analysis (DEA) in the presence of flexible measure.
- Publikační typ
- časopisecké články MeSH
Background: Super-resolution single molecule localization microscopy (SMLM) is a method for achieving resolution beyond the classical limit in optical microscopes (approx. 200 nm laterally). Yellow fluorescent protein (YFP) has been used for super-resolution single molecule localization microscopy, but less frequently than other fluorescent probes. Working with YFP in SMLM is a challenge because a lower number of photons are emitted per molecule compared with organic dyes, which are more commonly used. Publically available experimental data can facilitate development of new data analysis algorithms. Findings: Four complete, freely available single molecule super-resolution microscopy datasets on YFP-tagged growth factor receptors expressed in a human cell line are presented, including both raw and analyzed data. We report methods for sample preparation, for data acquisition, and for data analysis, as well as examples of the acquired images. We also analyzed the SMLM datasets using a different method: super-resolution optical fluctuation imaging (SOFI). The 2 modes of analysis offer complementary information about the sample. A fifth single molecule super-resolution microscopy dataset acquired with the dye Alexa 532 is included for comparison purposes. Conclusions: This dataset has potential for extensive reuse. Complete raw data from SMLM experiments have typically not been published. The YFP data exhibit low signal-to-noise ratios, making data analysis a challenge. These datasets will be useful to investigators developing their own algorithms for SMLM, SOFI, and related methods. The data will also be useful for researchers investigating growth factor receptors such as ErbB3.
- MeSH
- algoritmy MeSH
- bakteriální proteiny chemie MeSH
- fluorescenční barviva chemie MeSH
- lidé MeSH
- luminescentní proteiny chemie MeSH
- receptory růstových faktorů chemie izolace a purifikace MeSH
- zobrazení jednotlivé molekuly metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
This dataset provides longitudinal survey data from a European project, ySKILLS, which was focused on the role of digital skills in youths' development. It contains data from 10,821 participants from Grades 6-10 (in Wave 1) in Estonia, Finland, Germany, Italy, Poland, and Portugal. The data was collected between Spring 2021 and Spring 2023, the participants were recruited through schools, where the data collection also took place, except for online data collections due to restrictions caused by COVID-19. The dataset is novel in its multidimensional approach to the construct of digital literacy. It provides insight into the development of digital skills in youth and the role of digital skills and internet usage in youths' positive and negative online experiences and wellbeing. It also contains data that allows for the analysis of the role of digital skills in class networks. The data are beneficial for researchers interested in the examination of youths' online skills, internet usage, online experiences, and wellbeing from a longitudinal perspective.
- Publikační typ
- časopisecké články MeSH
Registration of laser scans, or point clouds in general, is a crucial step of localization and mapping with mobile robots or in object modeling pipelines. A coarse alignment of the point clouds is generally needed before applying local methods such as the Iterative Closest Point (ICP) algorithm. We propose a feature-based approach to point cloud registration and evaluate the proposed method and its individual components on challenging real-world datasets. For a moderate overlap between the laser scans, the method provides a superior registration accuracy compared to state-of-the-art methods including Generalized ICP, 3D Normal-Distribution Transform, Fast Point-Feature Histograms, and 4-Points Congruent Sets. Compared to the surface normals, the points as the underlying features yield higher performance in both keypoint detection and establishing local reference frames. Moreover, sign disambiguation of the basis vectors proves to be an important aspect in creating repeatable local reference frames. A novel method for sign disambiguation is proposed which yields highly repeatable reference frames.
- MeSH
- algoritmy MeSH
- datové soubory jako téma * MeSH
- robotika MeSH
- Publikační typ
- časopisecké články MeSH
PURPOSE: Despite the improvement of therapeutic regimens, several patients with multiple myeloma (MM) still experience early relapse (ER). This subset of patients currently represents an unmet medical need. EXPERIMENTAL DESIGN: We pooled data from seven European multicenter phase II/III clinical trials enrolling 2,190 patients with newly diagnosed MM from 2003 to 2017. Baseline patient evaluation included 14 clinically relevant features. Patients with complete data (n = 1,218) were split into training (n = 844) and validation sets (n = 374). In the training set, a univariate analysis and a multivariate logistic regression model on ER within 18 months (ER18) were made. The most accurate model was selected on the validation set. We also developed a dynamic version of the score by including response to treatment. RESULTS: The Simplified Early Relapse in Multiple Myeloma (S-ERMM) score was modeled on six features weighted by a score: 5 points for high lactate dehydrogenase or t(4;14); 3 for del17p, abnormal albumin, or bone marrow plasma cells >60%; and 2 for λ free light chain. The S-ERMM identified three patient groups with different risks of ER18: Intermediate (Int) versus Low (OR = 2.39, P < 0.001) and High versus Low (OR = 5.59, P < 0.001). S-ERMM High/Int patients had significantly shorter overall survival (High vs. Low: HR = 3.24, P < 0.001; Int vs. Low: HR = 1.86, P < 0.001) and progression-free survival-2 (High vs. Low: HR = 2.89, P < 0.001; Int vs. Low: HR = 1.76, P < 0.001) than S-ERMM Low. The Dynamic S-ERMM (DS-ERMM) modulated the prognostic power of the S-ERMM. CONCLUSIONS: On the basis of simple, widely available baseline features, the S-ERMM and DS-ERMM properly identified patients with different risks of ER and survival outcomes.
- MeSH
- časové faktory MeSH
- datové soubory jako téma MeSH
- lidé středního věku MeSH
- lidé MeSH
- míra přežití MeSH
- mnohočetný myelom mortalita terapie MeSH
- prognóza MeSH
- recidiva MeSH
- senioři MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- validační studie MeSH
We compiled data from histological sources on the formation ages for human mandibular and maxillary permanent first molars, lateral and central incisors and canines. From this we summarised the data by reporting weighted means for cusp initiation, crown completion and apex completion. This provides a reference for bioarchaeological and medical studies investigating early childhood. More specifically, this reference is a crucial element in the study of early childhood nutrition and morbidity from osteological analysis and stable isotope analyses of teeth and their growth increments.
- Publikační typ
- časopisecké články MeSH
Genetic association studies suggest a genetic predisposition for cisplatin-induced ototoxicity. Among other candidate genes, thiopurine methyltransferase (TPMT) is considered a critical gene for susceptibility to cisplatin-induced hearing loss in a pharmacogenetic guideline. The PanCareLIFE cross-sectional cohort study evaluated the genetic associations in a large pan-European population and assessed the diagnostic accuracy of the genetic markers. 1,112 pediatric cancer survivors who had provided biomaterial for genotyping were screened for participation in the pharmacogenetic association study. 900 participants qualified for inclusion. Based on the assessment of original audiograms, patients were assigned to three phenotype categories: no, minor, and clinically relevant hearing loss. Fourteen variants in eleven candidate genes (ABCC3, OTOS, TPMT, SLC22A2, NFE2L2, SLC16A5, LRP2, GSTP1, SOD2, WFS1, and ACYP2) were genotyped. The genotype and phenotype data represent a resource for conducting meta-analyses to derive a more precise pooled estimate of the effects of genes on the risk of hearing loss due to platinum treatment.
- Publikační typ
- časopisecké články MeSH
