Human TSCM cell dynamics in vivo are compatible with long-lived immunological memory and stemness.

Adaptive immunity relies on the generation and maintenance of memory T cells to provide protection against repeated antigen exposure. It has been hypothesised that a self-renewing population of T cells, named stem cell-like memory T (TSCM) cells, are responsible for maintaining memory. However, it is not clear if the dynamics of TSCM cells in vivo are compatible with this hypothesis. To address this issue, we investigated the dynamics of TSCM cells under physiological conditions in humans in vivo using a multidisciplinary approach that combines mathematical modelling, stable isotope labelling, telomere length analysis, and cross-sectional data from vaccine recipients. We show that, unexpectedly, the average longevity of a TSCM clone is very short (half-life < 1 year, degree of self-renewal = 430 days): far too short to constitute a stem cell population. However, we also find that the TSCM population is comprised of at least 2 kinetically distinct subpopulations that turn over at different rates. Whilst one subpopulation is rapidly replaced (half-life = 5 months) and explains the rapid average turnover of the bulk TSCM population, the half-life of the other TSCM subpopulation is approximately 9 years, consistent with the longevity of the recall response. We also show that this latter population exhibited a high degree of self-renewal, with a cell residing without dying or differentiating for 15% of our lifetime. Finally, although small, the population was not subject to excessive stochasticity. We conclude that the majority of TSCM cells are not stem cell-like but that there is a subpopulation of TSCM cells whose dynamics are compatible with their putative role in the maintenance of T cell memory

VE-statin/egfl7 Expression in Endothelial Cells Is Regulated by a Distal Enhancer and a Proximal Promoter under the Direct Control of Erg and GATA-2

Angiogenesis is the process by which new blood vessels arise from existing ones by the budding out of endothelial cell capillaries from the luminal side of blood vessels. Blood vessel formation is essential for organ development during embryogenesis and is associated with several physiological and pathological processes, such as wound healing and tumor development. The VE-statin/egfl7 gene is specifically expressed in endothelial cells during embryonic development and in the adult. We studied here the regulatory mechanisms that control this tissue-specific expression. RT-qPCR analyses showed that the specificity of expression of VE-statin/egfl7 in endothelial cells is not shared with its closest neighbor genes notch1 and agpat2 on the mouse chromosome 2. Chromatin-immunoprecipitation analysis of histone modifications at the VE-statin/egfl7 locus showed that the chromatin is specifically opened in endothelial cells, but not in fibroblasts at the transcription start sites. A 13 kb genomic fragment of promoter was cloned and analyzed by gene reporter assays which showed that two conserved regions are important for the specific expression of VE-statin/egfl7 in endothelial cells; a −8409/−7563 enhancer and the −252/+38 region encompassing the exon-1b transcription start site. The latter contains essential GATA and ETS-binding sites, as assessed by linker-scanning analysis and site-directed mutagenesis. An analysis of expression of the ETS and GATA transcription factors showed that Erg, Fli-1 and GATA-2 are the most highly expressed factors in endothelial cells. Erg and GATA-2 directly control the expression of the endogenous VE-statin/egfl7 while Fli-1 probably exerts an indirect control, as assessed by RNA interference and chromatin immunoprecipitation. This first detailed analysis of the mechanisms that govern the expression of the VE-statin/egfl7 gene in endothelial cells pinpoints the specific importance of ETS and GATA factors in the specific regulation of genes in this cell lineage

Measurement of the branching fraction ratios and CP asymmetries in B-→ D0 CP K-decays

We present a preliminary study of $B^- \to D^0_{CP} \pi^-$ and $B^- \to D^0_{CP} K^-$ decays, with the $D^0_{CP}$ reconstructed in the CP-odd eigenstates $K_s \pi^0$, $K_s \omega$, in the CP-even eigenstates $K^+ K^-$, $\pi^+ \pi^-$, and in the (non-CP) flavor eigenstate $K^\mp \pi^\pm$. Using a sample of about 382 million Y(4S) decays into BBbar pairs, collected with the BABAR detector operating at the PEP-II asymmetric-energy B Factory at SLAC, we measure the ratios of the branching fractions R_CP+- and the direct CP asymmetries A_CP+-. The results are: R_CP- = 0.81 \pm 0.10 (stat) \pm 0.05 (syst) R_CP+ = 1.07 \pm 0.10 (stat) \pm 0.04 (syst) A_CP- = -0.19 \pm 0.12 (stat) \pm 0.02 (syst) A_CP+ = 0.35 \pm 0.09 (stat) \pm 0.05 (syst

Measurement of branching fractions and charge asymmetries in B decays to an eta meson and a K-* meson

We present measurements of branching fractions and charge asymmetries for the decays B ->eta K-*, where K-* indicates a spin 0, 1, or 2 K pi system. The data sample corresponds to 344x10(6) B (B) over bar pairs collected with the BABAR detector at the PEP-II asymmetric-energy e(+)e(-) collider at SLAC. We measure the branching fractions (in units of 10(-6)): B(B-0 ->eta K-*0(892))=16.5 +/- 1.1 +/- 0.8, B(B+->eta K*+(892))=18.9 +/- 1.8 +/- 1.3, B(B-0 ->eta(K pi)(0)(*0))=11.0 +/- 1.6 +/- 1.5, B(B+->eta(K pi)(0)(*+))=18.2 +/- 2.6 +/- 2.6, B(B-0 ->eta K-2(*0)(1430))=9.6 +/- 1.8 +/- 1.1, and B(B+->eta K-2(*+)(1430))=9.1 +/- 2.7 +/- 1.4. We also determine the charge asymmetries for all decay modes

Search for the lepton flavour violating decay τ − → μ − μ + μ −

A search for the lepton flavour violating decay $\tau^-\to \mu^-\mu^+\mu^-$ is performed with the LHCb experiment. The data sample corresponds to an integrated luminosity of $1.0\mathrm{\,fb}^{-1}$ of proton-proton collisions at a centre-of-mass energy of $7\mathrm{\,Te\kern -0.1em V}$ and $2.0\mathrm{\,fb}^{-1}$ at $8\mathrm{\,Te\kern -0.1em V}$. No evidence is found for a signal, and a limit is set at $90\%$ confidence level on the branching fraction, $\mathcal{B}(\tau^-\to \mu^-\mu^+\mu^-) < 4.6 \times 10^{-8}$.Comment: 20 pages, 10 figures, published as JHEP 02 (2015) 12

Understanding the Sub-Cellular Dynamics of Silicon Transportation and Synthesis in Diatoms Using Population-Level Data and Computational Optimization

Controlled synthesis of silicon is a major challenge in nanotechnology and material science. Diatoms, the unicellular algae, are an inspiring example of silica biosynthesis, producing complex and delicate nano-structures. This happens in several cell compartments, including cytoplasm and silica deposition vesicle (SDV). Considering the low concentration of silicic acid in oceans, cells have developed silicon transporter proteins (SIT). Moreover, cells change the level of active SITs during one cell cycle, likely as a response to the level of external nutrients and internal deposition rates. Despite this topic being of fundamental interest, the intracellular dynamics of nutrients and cell regulation strategies remain poorly understood. One reason is the difficulties in measurements and manipulation of these mechanisms at such small scales, and even when possible, data often contain large errors. Therefore, using computational techniques seems inevitable. We have constructed a mathematical model for silicon dynamics in the diatom Thalassiosira pseudonana in four compartments: external environment, cytoplasm, SDV and deposited silica. The model builds on mass conservation and Michaelis-Menten kinetics as mass transport equations. In order to find the free parameters of the model from sparse, noisy experimental data, an optimization technique (global and local search), together with enzyme related penalty terms, has been applied. We have connected population-level data to individual-cell-level quantities including the effect of early division of non-synchronized cells. Our model is robust, proven by sensitivity and perturbation analysis, and predicts dynamics of intracellular nutrients and enzymes in different compartments. The model produces different uptake regimes, previously recognized as surge, externally-controlled and internally-controlled uptakes. Finally, we imposed a flux of SITs to the model and compared it with previous classical kinetics. The model introduced can be generalized in order to analyze different biomineralizing organisms and to test different chemical pathways only by switching the system of mass transport equations