Exploring non-adiabatic approximations to the exchange-correlation functional of TDDFT

A decomposition of the exact exchange-correlation potential of time-dependent density functional theory into an interaction component and a kinetic component offers a new starting point for non-adiabatic approximations. The components are expressed in terms of the exchange-correlation hole and the difference between the one-body density matrix of the interacting and Kohn-Sham systems, which must be approximated in terms of quantities accessible from the Kohn-Sham evolution. We explore several preliminary approximations, evaluate their fulfillment of known exact conditions, and test their performance on simple model systems for which available exact solutions indicate the significance of going beyond the adiabatic approximation.Fil: Fuks, Johanna Ildemar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Lacombe, Lionel. University of New York; Estados UnidosFil: Nielsen, Søren E. B.. Max Planck Institute for the Structure and Dynamics of Matter; Alemania. Center for Free-Electron Laser Science; AlemaniaFil: Maitra, Neepa T.. University of New York; Estados Unido

Relation between tetR and tetA expression in tetracycline resistant Escherichia coli

BACKGROUND: Tetracyclines are among the most used antibiotics in livestock worldwide. Resistance is widely disseminated in Escherichia coli, where it is generally mediated by tetracycline efflux pumps, such as TetA. Expression of tetracycline efflux pumps is tightly controlled by the repressor TetR, which has been shown to be tetracycline-responsive at sub-MIC tetracycline concentrations. The objective of this study was to investigate the effects of increasing tetracycline concentrations on the growth of TetA-producing E. coli, and to determine how expression of tetA and tetR related to each other in different growth phases in the presence of tetracycline. RESULTS: A tetracycline resistant E. coli strain containing tetA and tetR on the chromosome was constructed and cultured in the presence of increasing concentrations of tetracycline. Expression of tetR and tetA was measured at four time points in different growth phases by quantitative real-time PCR. The TetA-producing E. coli exhibited prolonged lag phase with increasing concentrations of tetracycline, while expression of tetA and tetR increased and decreased, respectively, with increasing tetracycline concentration. The levels of tetA and tetR mRNA varied depending on growth phase, resulting in a gradual decrease of the tetA/tetR ratio from approximately 4 in the lag phase to approximately 2 in the stationary phase. CONCLUSION: This study shows that the expression of tetR and tetA is tetracycline concentration- and growth phase-dependent, contributing to improved understanding of the relationships between E. coli growth, tetracycline exposure and expression of tetracycline resistance. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12866-016-0649-z) contains supplementary material, which is available to authorized users

CD163-L1 Is an Endocytic Macrophage Protein Strongly Regulated by Mediators in the Inflammatory Response

Abstract CD163-L1 belongs to the group B scavenger receptor cysteine-rich family of proteins, where the CD163-L1 gene arose by duplication of the gene encoding the hemoglobin scavenger receptor CD163 in late evolution. The current data demonstrate that CD163-L1 is highly expressed and colocalizes with CD163 on large subsets of macrophages, but in contrast to CD163 the expression is low or absent in monocytes and in alveolar macrophages, glia, and Kupffer cells. The expression of CD163-L1 increases when cultured monocytes are M-CSF stimulated to macrophages, and the expression is further increased by the acute-phase mediator IL-6 and the anti-inflammatory mediator IL-10 but is suppressed by the proinflammatory mediators IL-4, IL-13, TNF-α, and LPS/IFN-γ. Furthermore, we show that CD163-L1 is an endocytic receptor, which internalizes independently of cross-linking through a clathrin-mediated pathway. Two cytoplasmic splice variants of CD163-L1 are differentially expressed and have different subcellular distribution patterns. Despite its many similarities to CD163, CD163-L1 does not possess measurable affinity for CD163 ligands such as the haptoglobin–hemoglobin complex or various bacteria. In conclusion, CD163-L1 exhibits similarity to CD163 in terms of structure and regulated expression in cultured monocytes but shows clear differences compared with the known CD163 ligand preferences and expression pattern in the pool of tissue macrophages. We postulate that CD163-L1 functions as a scavenger receptor for one or several ligands that might have a role in resolution of inflammation.</jats:p

Does size really matter? A multisite study assessing the latent structure of the proposed ICD-11 and DSM-5 diagnostic criteria for PTSD

Background: Researchers and clinicians within the field of trauma have to choose between different diagnostic descriptions of posttraumatic stress disorder (PTSD) in the DSM-5 and the proposed ICD-11. Several studies support different competing models of the PTSD structure according to both diagnostic systems; however, findings show that the choice of diagnostic systems can affect the estimated prevalence rates. Objectives: The present study aimed to investigate the potential impact of using a large (i.e. the DSM-5) compared to a small (i.e. the ICD-11) diagnostic description of PTSD. In other words, does the size of PTSD really matter? Methods: The aim was investigated by examining differences in diagnostic rates between the two diagnostic systems and independently examining the model fit of the competing DSM-5 and ICD-11 models of PTSD across three trauma samples: university students (N = 4213), chronic pain patients (N = 573), and military personnel (N = 118). Results: Diagnostic rates of PTSD were significantly lower according to the proposed ICD-11 criteria in the university sample, but no significant differences were found for chronic pain patients and military personnel. The proposed ICD-11 three-factor model provided the best fit of the tested ICD-11 models across all samples, whereas the DSM-5 seven-factor Hybrid model provided the best fit in the university and pain samples, and the DSM-5 six-factor Anhedonia model provided the best fit in the military sample of the tested DSM-5 models. Conclusions: The advantages and disadvantages of using a broad or narrow set of symptoms for PTSD can be debated, however, this study demonstrated that choice of diagnostic system may influence the estimated PTSD rates both qualitatively and quantitatively. In the current described diagnostic criteria only the ICD-11 model can reflect the configuration of symptoms satisfactorily. Thus, size does matter when assessing PTSD

SNHG16 is regulated by the Wnt pathway in colorectal cancer and affects genes involved in lipid metabolism

It is well established that lncRNAs are aberrantly expressed in cancer where they have been shown to act as oncogenes or tumor suppressors. RNA profiling of 314 colorectal adenomas/adenocarcinomas and 292 adjacent normal colon mucosa samples using RNA‐sequencing demonstrated that the snoRNA host gene 16 (SNHG16) is significantly up‐regulated in adenomas and all stages of CRC. SNHG16 expression was positively correlated to the expression of Wnt‐regulated transcription factors, including ASCL2, ETS2, and c‐Myc. In vitro abrogation of Wnt signaling in CRC cells reduced the expression of SNHG16 indicating that SNHG16 is regulated by the Wnt pathway. Silencing of SNHG16 resulted in reduced viability, increased apoptotic cell death and impaired cell migration. The SNHG16 silencing particularly affected expression of genes involved in lipid metabolism. A connection between SNHG16 and genes involved in lipid metabolism was also observed in clinical tumors. Argonaute CrossLinking and ImmunoPrecipitation (AGO‐CLIP) demonstrated that SNHG16 heavily binds AGO and has 27 AGO/miRNA target sites along its length, indicating that SNHG16 may act as a competing endogenous RNA (ceRNA) “sponging” miRNAs off their cognate targets. Most interestingly, half of the miRNA families with high confidence targets on SNHG16 also target the 3′UTR of Stearoyl‐CoA Desaturase (SCD). SCD is involved in lipid metabolism and is down‐regulated upon SNHG16 silencing. In conclusion, up‐regulation of SNHG16 is a frequent event in CRC, likely caused by deregulated Wnt signaling. In vitro analyses demonstrate that SNHG16 may play an oncogenic role in CRC and that it affects genes involved in lipid metabolism, possible through ceRNA related mechanisms

Structural Properties of MHC Class II Ligands, Implications for the Prediction of MHC Class II Epitopes

Major Histocompatibility class II (MHC-II) molecules sample peptides from the extracellular space allowing the immune system to detect the presence of foreign microbes from this compartment. Prediction of MHC class II ligands is complicated by the open binding cleft of the MHC class II molecule, allowing binding of peptides extending out of the binding groove. Furthermore, only a few HLA-DR alleles have been characterized with a sufficient number of peptides (100–200 peptides per allele) to derive accurate description of their binding motif. Little work has been performed characterizing structural properties of MHC class II ligands. Here, we perform one such large-scale analysis. A large set of SYFPEITHI MHC class II ligands covering more than 20 different HLA-DR molecules was analyzed in terms of their secondary structure and surface exposure characteristics in the context of the native structure of the corresponding source protein. We demonstrated that MHC class II ligands are significantly more exposed and have significantly more coil content than other peptides in the same protein with similar predicted binding affinity. We next exploited this observation to derive an improved prediction method for MHC class II ligands by integrating prediction of MHC- peptide binding with prediction of surface exposure and protein secondary structure. This combined prediction method was shown to significantly outperform the state-of-the-art MHC class II peptide binding prediction method when used to identify MHC class II ligands. We also tried to integrate N- and O-glycosylation in our prediction methods but this additional information was found not to improve prediction performance. In summary, these findings strongly suggest that local structural properties influence antigen processing and/or the accessibility of peptides to the MHC class II molecule