The Algebra of the Energy-Momentum Tensor and the Noether Currents in Classical Non-Linear Sigma Models

The recently derived current algebra of classical non-linear sigma models on arbitrary Riemannian manifolds is extended to include the energy-momentum tensor. It is found that in two dimensions the energy-momentum tensor $\theta_{\mu\nu}$, the Noether current $j_\mu$ associated with the global symmetry of the theory and the composite field $j$ appearing as the coefficient of the Schwinger term in the current algebra, together with the derivatives of $j_\mu$ and $j$, generate a closed algebra. The subalgebra generated by the light-cone components of the energy-momentum tensor consists of two commuting copies of the Virasoro algebra, with central charge $\, c\!=\!0$, reflecting the classical conformal invariance of the theory, but the current algebra part and the semidirect product structure are quite different from the usual Kac-Moody / Sugawara type construction.Comment: 10 pages, THEP 92/2

Current Algebra of Classical Non-Linear Sigma Models

The current algebra of classical non-linear sigma models on arbitrary Riemannian manifolds is analyzed. It is found that introducing, in addition to the Noether current $j_\mu$ associated with the global symmetry of the theory, a composite scalar field $j$, the algebra closes under Poisson brackets.Comment: 6 page

Toxicokinetics and analytical toxicology of the abused opioid U-48800 - in vitro metabolism, metabolic stability, isozyme mapping, and plasma protein binding

Due to the risk of new synthetic opioids (NSOs) for human health, the knowledge of their toxicokinetic characteristics is important for clinical and forensic toxicology. U‐48800 is an NSO structurally non‐related to classical opioids such as morphine or fentanyl and offered for abuse. As toxicokinetic data of U‐48800 is not currently available, the aims of this study were to identify the in vitro metabolites of U‐48800 in pooled human liver S9 fraction (pS9), to map the isozymes involved in the initial metabolic steps, and to determine further toxicokinetic data such as metabolic stability, including the in vitro half‐life (t1/2), and the intrinsic (CLint) and hepatic clearance (CLh). Furthermore, drug detectability studies in rat urine should be done using hyphenated mass spectrometry. In total, 13 phase I metabolites and one phase II metabolite were identified. N‐Dealkylation, hydroxylation, and their combinations were the predominant metabolic reactions. The isozymes CYP2C19 and CYP3A4 were mainly involved in these initial steps. CYP2C19 poor metabolizers may suffer from an increased U‐48800 toxicity. The in vitro t1/2 and CLint could be rated as moderate, compared to structural related compounds. After administration of an assumed consumer dose to rats, the unchanged parent compound was found only in very low abundance but three metabolites were detected additionally. Due to species differences, metabolites found in rats might be different from those in humans. However, phase I metabolites found in rat urine, the parent compound, and additionally the N‐demethyl metabolite should be used as main targets in toxicological urine screening approaches

Cell division protein FtsK coordinates bacterial chromosome segregation and daughter cell separation in Staphylococcus aureus

Funding Information: We thank Nathalie Reichmann and Leendert Hamoen (University of Amsterdam) for critical reading of the manuscript, Ana Velic (Proteome Center Tübingen) for help with proteome analysis and Mike VanNieuwenhze (Indiana University) for the generous gift of HADA. This study was funded by the European Research Council through grant ERC‐2017‐CoG‐771709 (to MGP), by national funds through FCT– Fundação para a Ciência e a Tecnologia, PTDC/BIA‐MIC/6982/2020 (to HV); PTDC/BIA‐PLA/3432/2012 (to SRF); FCT through MOSTMICRO‐ITQB R&D Unit (UIDB/04612/2020, UIDP/04612/2020) and LS4FUTURE Associated Laboratory (LA/P/0087/2020) and FCT fellowship SFRH/BD/147052/2019 (to BMS); by the Swiss National National Foundation through P300P3_155346 (to AJ); by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska‐Curie grant agreement No 839596 (to SS) and by the European Molecular Biology Organization through award ALTF 673‐2018 (to SS). Figure 6D and Appendix Fig S7 were created with Biorender.com . Funding Information: We thank Nathalie Reichmann and Leendert Hamoen (University of Amsterdam) for critical reading of the manuscript, Ana Velic (Proteome Center Tübingen) for help with proteome analysis and Mike VanNieuwenhze (Indiana University) for the generous gift of HADA. This study was funded by the European Research Council through grant ERC-2017-CoG-771709 (to MGP), by national funds through FCT– Fundação para a Ciência e a Tecnologia, PTDC/BIA-MIC/6982/2020 (to HV); PTDC/BIA-PLA/3432/2012 (to SRF); FCT through MOSTMICRO-ITQB R&D Unit (UIDB/04612/2020, UIDP/04612/2020) and LS4FUTURE Associated Laboratory (LA/P/0087/2020) and FCT fellowship SFRH/BD/147052/2019 (to BMS); by the Swiss National National Foundation through P300P3_155346 (to AJ); by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 839596 (to SS) and by the European Molecular Biology Organization through award ALTF 673-2018 (to SS). Figure 6D and Appendix Fig S7 were created with Biorender.com. Publisher Copyright: © 2023 The Authors. Published under the terms of the CC BY NC ND 4.0 license.Unregulated cell cycle progression may have lethal consequences and therefore, bacteria have various mechanisms in place for the precise spatiotemporal control of cell cycle events. We have uncovered a new link between chromosome replication/segregation and splitting of the division septum. We show that the DNA translocase domain-containing divisome protein FtsK regulates cellular levels of a peptidoglycan hydrolase Sle1, which is involved in cell separation in the bacterial pathogen Staphylococcus aureus. FtsK interacts with a chaperone (trigger factor, TF) and establishes a FtsK-dependent TF concentration gradient that is higher in the septal region. Trigger factor binds Sle1 and promotes its preferential export at the septal region, while also preventing Sle1 degradation by the ClpXP proteolytic machinery. Upon conditions that lead to paused septum synthesis, such as DNA damage or impaired DNA replication/segregation, TF gradient is dissipated and Sle1 levels are reduced, thus halting premature septum splitting.publishersversionpublishe

Elevated nerve growth factor and neurotrophin-3 levels in cerebrospinal fluid of children with hydrocephalus

BACKGROUND: Elevated intracranial pressure (ICP) resulting from impaired drainage of cerebrospinal fluid (CSF) causes hydrocephalus with damage to the central nervous system. Clinical symptoms of elevated intracranial pressure (ICP) in infants may be difficult to diagnose, leading to delayed treatment by shunt placement. Until now, no biochemical marker of elevated ICP has been available for clinical diagnosis and monitoring. In experimental animal models, nerve growth factor (NGF) and neurotrophin-3 (NT-3) have been shown to be produced by glial cells as an adaptive response to hypoxia. We investigated whether concentrations of NGF and NT-3 are increased in the CSF of children with hydrocephalus. METHODS: NGF was determined in CSF samples collected from 42 hydrocephalic children on 65 occasions (taps or shunt placement surgery). CSF samples obtained by lumbar puncture from 22 children with suspected, but unconfirmed bacterial infection served as controls. Analysis was performed using ELISA techniques. RESULTS: NGF concentrations in hydrocephalic children were over 50-fold increased compared to controls (median 225 vs 4 pg/mL, p < 0.0001). NT-3 was detectable (> 1 pg/mL) in 14/31 hydrocephalus samples at 2–51 pg/mL but in none of 11 control samples (p = 0.007). CONCLUSION: NGF and NT-3 concentrations are increased in children with hydrocephalus. This may represent an adaptive response of the brain to elevated ICP

Correlation of SHOX2 Gene Amplification and DNA Methylation in Lung Cancer Tumors

<p>Abstract</p> <p>Background</p> <p>DNA methylation in the <it>SHOX2 </it>locus was previously used to reliably detect lung cancer in a group of critical controls, including 'cytologically negative' samples with no visible tumor cell content, at a high specificity based on the analysis of bronchial lavage samples. This study aimed to investigate, if the methylation correlates with <it>SHOX2 </it>gene expression and/or copy number alterations. An amplification of the <it>SHOX2 </it>gene locus together with the observed tumor-specific hypermethylation might explain the good performance of this marker in bronchial lavage samples.</p> <p>Methods</p> <p><it>SHOX2 </it>expression, gene copy number and DNA methylation were determined in lung tumor tissues and matched morphologically normal adjacent tissues (NAT) from 55 lung cancer patients. Quantitative HeavyMethyl (HM) real-time PCR was used to detect <it>SHOX2 </it>DNA methylation levels. <it>SHOX2 </it>expression was assayed with quantitative real-time PCR, and copy numbers alterations were measured with conventional real-time PCR and array CGH.</p> <p>Results</p> <p>A hypermethylation of the <it>SHOX2 </it>locus in tumor tissue as compared to the matched NAT from the same patient was detected in 96% of tumors from a group of 55 lung cancer patients. This correlated highly significantly with the frequent occurrence of copy number amplification (p < 0.0001), while the expression of the <it>SHOX2 </it>gene showed no difference.</p> <p>Conclusions</p> <p>Frequent gene amplification correlated with hypermethylation of the <it>SHOX2 </it>gene locus. This concerted effect qualifies <it>SHOX2 </it>DNA methylation as a biomarker for lung cancer diagnosis, especially when sensitive detection is needed, i.e. in bronchial lavage or blood samples.</p

Problems with Using the Normal Distribution – and Ways to Improve Quality and Efficiency of Data Analysis

Background: The Gaussian or normal distribution is the most established model to characterize quantitative variation of original data. Accordingly, data are summarized using the arithmetic mean and the standard deviation, by x 6 SD, or with the standard error of the mean, x 6 SEM. This, together with corresponding bars in graphical displays has become the standard to characterize variation. Methodology/Principal Findings: Here we question the adequacy of this characterization, and of the model. The published literature provides numerous examples for which such descriptions appear inappropriate because, based on the ‘‘95 % range check’’, their distributions are obviously skewed. In these cases, the symmetric characterization is a poor description and may trigger wrong conclusions. To solve the problem, it is enlightening to regard causes of variation. Multiplicative causes are by far more important than additive ones, in general, and benefit from a multiplicative (or log-) normal approach. Fortunately, quite similar to the normal, the log-normal distribution can now be handled easily and characterized at the level of the original data with the help of both, a new sign, x /, times-divide, and notation. Analogous to x 6 SD, it connects the multiplicative (or geometric) mean x * and the multiplicative standard deviation s * in the form x * x /s*, that is advantageous and recommended. Conclusions/Significance: The corresponding shift from the symmetric to the asymmetric view will substantially increas