Search Results (5)

Background/Objectives: Ibrutinib is a selective Bruton’s tyrosine kinase inhibitor approved for the treatment of chronic lymphocytic leukemia (CLL). This drug exhibits significant variability in response and toxicity profile, possibly due to genetic polymorphisms in drug-metabolizing enzymes and transporters. The aim of this observational study is to address interindividual variability in the efficacy and safety of ibrutinib treatment in 49 CLL patients. Methods: Genotyping of nine polymorphisms was performed by quantitative polymerase chain reaction (qPCR) using a ViiA7^® PCR Instrument and TaqMan assays, and ibrutinib plasma concentrations were determined using high-performance liquid chromatography coupled to a tandem mass spectrometry detector (HPLC-MS/MS). Results: Our study confirmed a high response rate, with 62% of patients achieving complete remission (CR), 9% CR with incomplete hematologic recovery (CRi), and 24% partial remission (PR). The impact of genetic polymorphisms on the CR rate was evaluated, revealing no statistically significant associations for CYP3A4, CYP3A5, ABCB1, ABCG2, and SLCO1B1 variants. However, a tendency was observed for patients carrying ABCB1 rs1128503, rs1045642 T/T, or rs2032582 A/A genotypes to achieve a higher CR rate. Adverse drug reactions (ADRs) were frequent, with vascular disorders (39%) and infections (27%) being the most common. Genetic polymorphisms influenced ibrutinib toxicity, with CYP3A4 *1/*22 appearing to be protective against overall ADRs. Conclusions: The unexpected association between CYP3A4 *1/*22 genotype and lower ADR incidence, as well as the trend toward improved treatment response in patients carrying ABCB1 genotypes, suggests compensatory metabolic mechanisms. However, given the small sample size, larger studies are needed to confirm these findings and their clinical implications, while also aiming to uncover other non-genetic factors that may contribute to a better understanding of the variability in treatment response and toxicity. Full article

Dental caries is a widespread issue impacting global oral health. White spot lesions, the earliest stage of caries, compromise enamel’s esthetics and integrity. Remineralization therapies, both fluoride and non-fluoride based, aim to restore enamel, but limited comparative data exist on their effects on lesion depth and microhardness. Thus, the aim of this systematic review was to evaluate the efficacy of remineralizing agents on lesion depth and microhardness of human teeth. The literature search included the following five databases: PubMed, Web of Science, Scielo, SCOPUS, and EMBASE from the period 2012 to October 2022. Studies evaluating lesion depth and microhardness in human teeth after the application of a remineralizing agent were considered for review. The meta-analysis was performed using RevMan 5.4 (The Cochrane Collaboration, Copenhagen, Denmark). A random effect model was used to pool estimate of effect and its 95% confidence intervals (CIs) for surface microhardness and depth lesion. Subgroup analyses were performed considering the presence of fluoride or not in the remineralization agent. Thirty-three studies were included in the qualitative review. Of these, twenty-six studies were included in the meta-analysis. The main risks of bias associated with the studies included a lack of blinding of the test operator and failure to obtain sample size. To conclude, fluorinated agents are more effective in remineralizing artificially induced white spot lesion than non-fluoride remineralizing agents. Full article

Fatigue is one of the most disabling symptoms in several neurological disorders and has an important cognitive component. However, the relationship between self-reported cognitive fatigue and objective cognitive assessment results remains elusive. Patients with post-COVID syndrome often report fatigue and cognitive issues several months after the acute infection. We aimed to develop predictive models of fatigue using neuropsychological assessments to evaluate the relationship between cognitive fatigue and objective neuropsychological assessment results. We conducted a cross-sectional study of 113 patients with post-COVID syndrome, assessing them with the Modified Fatigue Impact Scale (MFIS) and a comprehensive neuropsychological battery including standardized and computerized cognitive tests. Several machine learning algorithms were developed to predict MFIS scores (total score and cognitive fatigue score) based on neuropsychological test scores. MFIS showed moderate correlations only with the Stroop Color–Word Interference Test. Classification models obtained modest F1-scores for classification between fatigue and non-fatigued or between 3 or 4 degrees of fatigue severity. Regression models to estimate the MFIS score did not achieve adequate R² metrics. Our study did not find reliable neuropsychological predictors of cognitive fatigue in the post-COVID syndrome. This has important implications for the interpretation of fatigue and cognitive assessment. Specifically, MFIS cognitive domain could not properly capture actual cognitive fatigue. In addition, our findings suggest different pathophysiological mechanisms of fatigue and cognitive dysfunction in post-COVID syndrome. Full article

Given the interest in the study of metadiscourse as the communication of ideas and the way people use language in different communicative situations, this paper attempted to find the degree of confluence between metadiscourse markers from different studies and to show how patterns of metadiscourse analysis based on various written genres can be applied to a wider range. The mean values for the frequency of marker use and their respective deviations were determined by comparing a significant number of studies on metadiscourse elements. To ensure comparability, those following Hyland’s model were chosen. The units of analysis were grouped into two broad categories based on discursive characteristics: Academic genres (research articles, theses, and textbooks) and non-academic genres, which included documents ranging from newspaper editorials or opinion columns to Internet texts and other forms of digital communication. The results of our study highlight that the disparity in interactive markers between academic and non-academic texts is relatively small. This difference has been identified by previous studies, and it is confirmed herein that the difference may be related to the use of academic language, the topic, or the object of study. In contrast, the mean values of the interactive markers in non-academic texts are considerably higher than those in academic texts. At the same time, the texts seem to be organised along two axes (interactional and interactive) in distinct areas. Despite our initial assumptions that the data would be subject to individual variations, that differences would be found between different sections of the same genre within the same academic discipline, and that the results would vary if certain texts were added or excluded, we observed certain trends in the behaviour of the documents, although it prevailed that, within each category, the texts should be studied individually. Full article

The use of inclusive language, among many other gender equality initiatives in society, has garnered great attention in recent years. Gender equality offices in universities and public administration cannot cope with the task of manually checking the use of non-inclusive language in the documentation that those institutions generate. In this research, an automated solution for the detection of non-inclusive uses of the Spanish language in doctoral theses generated in Spanish universities is introduced using machine learning techniques. A large dataset has been used to train, validate, and analyze the use of inclusive language; the result is an algorithm that detects, within any Spanish text document, non-inclusive uses of the language with error, false positive, and false negative ratios slightly over 10%, and precision, recall, and F-measure percentages over 86%. Results also show the evolution with time of the ratio of non-inclusive usages per document, having a pronounced reduction in the last years under study. Full article