The Warburg effect is characterised by increased glucose uptake and lactate secretion in cancer cells resulting from metabolic transformation in tumour tissue. The corresponding molecular pathways switch from oxidative phosphorylation to aerobic glycolysis, due to changes in glucose degradation mechanisms known as the 'Warburg reprogramming' of cancer cells. https://www.selleckchem.com/products/n6-methyladenosine.html Key glycolytic enzymes, glucose transporters and transcription factors involved in the Warburg transformation are frequently dysregulated during carcinogenesis considered as promising diagnostic and prognostic markers as well as treatment targets. Flavonoids are molecules with pleiotropic activities. The metabolism-regulating anticancer effects of flavonoids are broadly demonstrated in preclinical studies. Flavonoids modulate key pathways involved in the Warburg phenotype including but not limited to PKM2, HK2, GLUT1 and HIF-1. The corresponding molecular mechanisms and clinical relevance of 'anti-Warburg' effects of flavonoids are discussed in this review article. The most prominent examples are provided for the potential application of targeted 'anti-Warburg' measures in cancer management. Individualised profiling and patient stratification are presented as powerful tools for implementing targeted 'anti-Warburg' measures in the context of predictive, preventive and personalised medicine.Artificial intelligence (AI) approaches pose a great opportunity for individualized, pre-symptomatic disease diagnosis which plays a key role in the context of personalized, predictive, and finally preventive medicine (PPPM). However, to translate PPPM into clinical practice, it is of utmost importance that AI-based models are carefully validated. The validation process comprises several steps, one of which is testing the model on patient-level data from an independent clinical cohort study. However, recruitment criteria can bias statistical analysis of cohort study data and impede model application beyond the training data. To evaluate whether and how data from independent clinical cohort studies differ from each other, this study systematically compares the datasets collected from two major dementia cohorts, namely, the Alzheimer's Disease Neuroimaging Initiative (ADNI) and AddNeuroMed. The presented comparison was conducted on individual feature level and revealed significant differences among both cohortspresents a proof of concept that reliable models for personalized predictive diagnostics are feasible, which, in turn, could lead to adequate disease prevention and hereby enable the PPPM paradigm in the dementia field.This article identifies diverse rationales to call for anticipatory governance of solar geoengineering, in light of a climate crisis. In focusing on governance rationales, we step back from proliferating debates in the literature on 'how, when, whom, and where' to govern, to address the important prior question of why govern solar geoengineering in the first place to restrict or enable its further consideration? We link these opposing rationales to contrasting underlying visions of a future impacted by climate change. These visions see the future as either more or less threatening, depending upon whether it includes the possible future use of solar geoengineering. Our analysis links these contrasting visions and governance rationales to existing governance proposals in the literature. In doing so, we illustrate why some proposals differ so significantly, while also showing that similar-sounding proposals may emanate from quite distinct rationales and thus advance different ends, depending upon how they are designed in practice.Stress and threats have been shown to influence our cognition and performance. In a preregistered online experiment (N = 446), we examined whether thinking about the ongoing covid-19 pandemic influences creative (insight problem solving) and analytic thinking. We found no support for our a-priori hypothesized effect (decrease in insight problem solving and no change in analytical thinking), however, several unpredicted results emerged. Exploratory analyses revealed that both types of thinking were harmed, yet only in men. Interestingly, the effect of exposure on thinking about covid-19 was indirect and led to careless task completion - again, only in men. We discuss these intriguing results and propose potential explanations along with future studies directions. Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR TKIs) are effective against classical mutations in lung cancer. However, their effectiveness and the prognosis of lung cancer patients with complex mutations are not well delineated. Therefore, we aimed to investigate the treatment effectiveness of different EGFR TKIs in patients with complex mutations. From 2005 to 2020, we collected lung adenocarcinoma tissue samples for mutation analysis using direct Sanger sequencing. Patients with mutations treated with EGFR TKIs as first-line treatment were enrolled. Clinical characteristics, mutation status, treatment response, progression-free survival (PFS), and overall survival (OS) were analyzed. Among 2675 patients with mutations, 239 (8.9%) had complex mutations, of whom 125 received EGFR TKI treatment as first-line treatment. Multivariate analysis revealed that afatinib was a more favorable factor for PFS than gefitinib [hazard ratio (HR), 2.01; 95% confidence interval (CI), 1.11-3.62] and erlotinib (HR, 2.61; 95% CI, 1.31-5.22), especially in patients with uncommon mutation patterns. Afatinib treatment as first-line treatment was also associated with longer OS compared with erlotinib (HR, 2.48; 95% CI, 1.20-5.12). Classical mutation pattern was associated with longer PFS (  = 0.001) and OS (  = 0.020). Secondary T790M was detected in 22 of 52 (42.3%) patients who had re-biopsied tissue samples after acquiring resistance to EGFR TKIs. There was no significant difference in secondary T790M formation after acquired resistance to the three EGFR TKIs (  = 0.261). Furthermore, three (5.8%) patients had small-cell lung cancer transformation. Afatinib is an effective first-line treatment for patients with lung adenocarcinoma harboring complex mutations, especially those with uncommon mutation patterns. Afatinib is an effective first-line treatment for patients with lung adenocarcinoma harboring complex EGFR mutations, especially those with uncommon mutation patterns.