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This work investigated patient-specific genomic BCR-ABL1 fusions as markers of measurable residual disease (MRD) in chronic myeloid leukaemia, with a focus on relevance to treatment-free remission (TFR) after achievement of deep molecular response (DMR) on tyrosine kinase inhibitor (TKI) therapy. DNA and mRNA BCR-ABL1 measurements by qPCR were compared in 2189 samples (129 patients) and by digital PCR in 1279 sample (62 patients). A high correlation was found at levels of disease above MR4, but there was a poor correlation for samples during DMR. A combination of DNA and RNA MRD measurements resulted in a better prediction of molecular relapse-free survival (MRFS) after TKI stop (n = 17) or scheduled interruption (n = 25). At 18 months after treatment cessation, patients with stopped or interrupted TKI therapy who were DNA negative/RNA negative during DMR maintenance (green group) had an MRFS of 80% and 100%, respectively, compared with those who were DNA positive/RNA negative (MRFS = 57% and 67%, respectively; yellow group) or DNA positive/RNA positive (MRFS = 20% for both cohorts; red group). Thus, we propose a “traffic light” stratification as a TFR predictor based on DNA and mRNA BCR-ABL1 measurements during DMR maintenance before TKI cessation.

This article investigates the distribution and typology of commas in Czech texts, combining genre-differentiated samples with an annotated error corpus to offer a comprehensive view of punctuation usage and misuse. Building on previous work, we expand the analysis from a small newspaper sample to a broader set of texts, encompassing fiction, blogs, translations, and school dictations. Using a consistent typology of comma usage, we classify 1,000 manually selected instances and identify trends in different textual genres. Furthermore, we examine over 1,000 missing comma errors and more than 200 redundant ones from the self-built error corpus. The results reveal genre-dependent tendencies in comma types, especially in the use of commas preceding connectives and within asyndetic structures. The study offers insights for improving automatic comma insertion systems and deepens our understanding of punctuation norms and deviations in Czech.

The demand for accurate and error-free written communication in Czech has led to the development of automated proofreading tools. Beta Opravidlo, a rule-based online proofreader launched in 2022, demonstrated high precision and recall in correcting Czech texts. However, its reliance on predefined linguistic rules limited recall and processing speed. With advancements in machine learning and large language models (LLMs), a transition toward AI-powered proofreading became necessary. This article explores the evolution from Beta Opravidlo to Opravidlo 2.0, integrating deep neural networks to enhance correction capabilities. We discuss proofreading as a machine learning task, compare traditional rule-based and neural approaches, and challenges such as explainability, system integration or computational requirements. The most effective solution is a hybrid approach combining rule-based precision with AI-driven adaptability. Opravidlo 2.0 aims to improve recall, optimize inference time, and extend support to other Slavic languages. This interdisciplinary effort highlights the potential of AI-powered proofreading to set new standards in language correction and usability.

Several studies have reported that chronic myeloid leukaemia (CML) patients expressing e14a2 BCR::ABL1 have a faster molecular response to therapy compared to patients expressing e13a2. To explore the reason for this difference we undertook a detailed technical comparison of the commonly used Europe Against Cancer (EAC) BCR::ABL1 reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) assay in European Treatment and Outcome Study (EUTOS) reference laboratories (n = 10). We found the amplification ratio of the e13a2 amplicon was 38% greater than e14a2 (p = 0.015), and the amplification efficiency was 2% greater (P = 0.17). This subtle difference led to measurable transcript-type dependent variation in estimates of residual disease which could be corrected by (i) taking the qPCR amplification efficiency into account, (ii) using alternative RT-qPCR approaches or (iii) droplet digital PCR (ddPCR), a technique which is relatively insensitive to differences in amplification kinetics. In CML patients, higher levels of BCR::ABL1/GUSB were identified at diagnosis for patients expressing e13a2 (n = 67) compared to e14a2 (n = 78) when analysed by RT-qPCR (P = 0.0005) but not ddPCR (P = 0.5). These data indicate that widely used RT-qPCR assays result in subtly different estimates of disease depending on BCR::ABL1 transcript type; these differences are small but may need to be considered for optimal patient management.

Standardized monitoring of BCR::ABL1 mRNA levels is essential for the management of chronic myeloid leukemia (CML) patients. From 2016 to 2021 the European Treatment and Outcome Study for CML (EUTOS) explored the use of secondary, lyophilized cell-based BCR::ABL1 reference panels traceable to the World Health Organization primary reference material to standardize and validate local laboratory tests. Panels were used to assign and validate conversion factors (CFs) to the International Scale and assess the ability of laboratories to assess deep molecular response (DMR). The study also explored aspects of internal quality control. The percentage of EUTOS reference laboratories (n = 50) with CFs validated as optimal or satisfactory increased from 67.5% to 97.6% and 36.4% to 91.7% for ABL1 and GUSB, respectively, during the study period and 98% of laboratories were able to detect MR4.5 in most samples. Laboratories with unvalidated CFs had a higher coefficient of variation for BCR::ABL1IS and some laboratories had a limit of blank greater than zero which could affect the accurate reporting of DMR. Our study indicates that secondary reference panels can be used effectively to obtain and validate CFs in a manner equivalent to sample exchange and can also be used to monitor additional aspects of quality assurance.

PurposeThe advent of tyrosine kinase inhibitor (TKI) therapies has revolutionized the treatment of chronic myeloid leukemia (CML). The European LeukemiaNet (ELN) recommends quantification of BCR–ABL1 transcripts by real-time quantitative PCR every 3 months during TKI treatment. Since a proportion of patients in deep molecular response (DMR: MR4, MR4.5, MR5) maintain remission after treatment stop, assessment of DMR is crucial. However, systematically collected molecular data, monitored with sensitive standardized assays, are not available outside clinical trials.MethodsData were collected on the standardized assessment of molecular response in the context of real-life practice. BCR–ABL1 transcript levels after > 2 years of TKI therapy were evaluated for DMR by local laboratories as well as standardized EUTOS laboratories. Since standardized molecular monitoring is a prerequisite for treatment discontinuation, central surveillance of the performance of the participating laboratories was carried out.ResultsBetween 2014 and 2017, 3377 peripheral blood samples from 1117 CML patients were shipped to 11 standardized reference laboratories in six European countries. BCR–ABL1 transcript types were b3a2 (41.63%), b2a2 (29.99%), b2a2/b3a2 (3.58%) and atypical (0.54%). For 23.72% of the patients, the initial transcript type had not been reported. Response levels (EUTOS laboratory) were: no MMR, n = 197 (6.51%); MMR, n = 496 (16.40%); MR4, n = 685 (22.64%); MR4.5, n = 937 (30.98%); MR5, n = 710 (23.47%). With a Cohen’s kappa coefficient of 0.708, a substantial agreement between EUTOS-certified and local laboratories was shown.ConclusionsMulticenter DMR assessment is feasible in the context of real-life clinical practice in Europe. Information on the BCR–ABL1 transcript type at diagnosis is crucial to accurately monitor patients’ molecular response during or after TKI therapy.

The aim of our paper is to demonstrate the procedures by which the data needed to refine tools for automatic morphological analysis of Czech can be obtained using a corpus, namely the Araneum Bohemicum IV Maximum (Czech, 20.03) 7.10 G web corpus of the ARANEA series and Araneum Bohemicum Maximum (Czech, 15.04) 3,20 G (hereinafter Araneum). Particularly, we will focus on propria of the Kladenští type, i.e., substantivized adjectives of denoting groups of persons according to affiliation. The goal of the probe into the Aranea web corpus is: 1) a corpus-based description of frequented properties of the type, which can be used as a starting point for rule disambiguation; 2) creating a list of the most frequent lemmas belonging to the type, which can then be included into dictionaries of automatic morphological analyzers (e.g. the MorfFlex dictionary by Hajič and Hlaváčová). We believe that the probe can help improve the results of tools for automatic morphological analysis of Czech.