Protein dynamics at slow timescales in engineered ß-lactamases does not limit evolvability

Understanding the underlying mechanisms in the evolution of new protein functions is key to better directing enzyme engineering efforts. Intragenic epistasis (the non-additive interaction of mutations affecting function) is a key feature of protein evolution. For example, in TEM-1 ß-lactamase, the mutations E104K and G238S show positive epistasis in that their combination show a greater than expected increase in antibiotic resistance1. Here, we aim to understand the impact of protein dynamics at slow timescales on epistasis. Large conformational rearrangements associated with ligand-binding, turnover of substrate or allostery occur at this timescale2. The readily evolvable antibiotic-resistant TEM-1 ß-lactamase and two of its variants that are more dynamic at slow timescales serve as models for this study. Our models show similar catalytic activity and substrate recognition, thermal stability, as well as conserved motions in fast (ps-ns) and intermediate (ns-ms) timescales but different motions at slow timescales (ms-ms)123. Please click Additional Files below to see the full abstract

Reduced-symmetry two-dimensional solitons in photonic lattices

We demonstrate theoretically and experimentally a novel type of localized beams supported by the combined effects of total internal and Bragg reflection in nonlinear two-dimensional square periodic structures. Such localized states exhibit strong anisotropy in their mobility properties, being highly mobile in one direction and trapped in the other, making them promising candidates for optical routing in nonlinear lattices.Comment: 5 pages, 4 figure

Adapting SAM for CDF

The CDF and D0 experiments probe the high-energy frontier and as they do so have accumulated hundreds of Terabytes of data on the way to petabytes of data over the next two years. The experiments have made a commitment to use the developing Grid based on the SAM system to handle these data. The D0 SAM has been extended for use in CDF as common patterns of design emerged to meet the similar requirements of these experiments. The process by which the merger was achieved is explained with particular emphasis on lessons learned concerning the database design patterns plus realization of the use cases.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 4 pages, pdf format, TUAT00

Heavy Flavours in Collider Experiments

Current issues in the studies of Heavy Flavours in colliders are described with particular emphasis on experiments in which the UK is involved. Results on charm production at HERA are examined and compared to those at the Tevatron. B production rates at the Tevatron as well as the status of B lifetimes and mixing in the LEP collaborations and at the Tevatron are highlighted. The measurement of sin2beta from CDF is described as well as the most recent results on top physics at the Tevatron

Application of deep learning models to improve ulcerative colitis endoscopic disease activity scoring under multiple scoring systems

Background and Aims Lack of clinical validation and inter-observer variability are two limitations of endoscopic assessment and scoring of disease severity in patients with ulcerative colitis [UC]. We developed a deep learning [DL] model to improve, accelerate and automate UC detection, and predict the Mayo Endoscopic Subscore [MES] and the Ulcerative Colitis Endoscopic Index of Severity [UCEIS]. Methods A total of 134 prospective videos [1550 030 frames] were collected and those with poor quality were excluded. The frames were labelled by experts based on MES and UCEIS scores. The scored frames were used to create a preprocessing pipeline and train multiple convolutional neural networks [CNNs] with proprietary algorithms in order to filter, detect and assess all frames. These frames served as the input for the DL model, with the output being continuous scores for MES and UCEIS [and its components]. A graphical user interface was developed to support both labelling video sections and displaying the predicted disease severity assessment by the artificial intelligence from endoscopic recordings. Results Mean absolute error [MAE] and mean bias were used to evaluate the distance of the continuous model’s predictions from ground truth, and its possible tendency to over/under-predict were excellent for MES and UCEIS. The quadratic weighted kappa used to compare the inter-rater agreement between experts’ labels and the model’s predictions showed strong agreement [0.87, 0.88 at frame-level, 0.88, 0.90 at section-level and 0.90, 0.78 at video-level, for MES and UCEIS, respectively]. Conclusions We present the first fully automated tool that improves the accuracy of the MES and UCEIS, reduces the time between video collection and review, and improves subsequent quality assurance and scoring

Bi-allelic Variants in the GPI Transamidase Subunit PIGK Cause a Neurodevelopmental Syndrome with Hypotonia, Cerebellar Atrophy, and Epilepsy

Glycosylphosphatidylinositol (GPI)-anchored proteins are critical for embryogenesis, neurogenesis, and cell signaling. Variants in several genes participating in GPI biosynthesis and processing lead to decreased cell surface presence of GPI-anchored proteins (GPI-APs) and cause inherited GPI deficiency disorders (IGDs). In this report, we describe 12 individuals from nine unrelated families with 10 different bi-allelic PIGK variants. PIGK encodes a component of the GPI transamidase complex, which attaches the GPI anchor to proteins. Clinical features found in most individuals include global developmental delay and/or intellectual disability, hypotonia, cerebellar ataxia, cerebellar atrophy, and facial dysmorphisms. The majority of the individuals have epilepsy. Two individuals have slightly decreased levels of serum alkaline phosphatase, while eight do not. Flow cytometric analysis of blood and fibroblasts from affected individuals showed decreased cell surface presence of GPI-APs. The overexpression of wild-type (WT) PIGK in fibroblasts rescued the levels of cell surface GPI-APs. In a knockout cell line, transfection with WT PIGK also rescued the GPI-AP levels, but transfection with the two tested mutant variants did not. Our study not only expands the clinical and known genetic spectrum of IGDs, but it also expands the genetic differential diagnosis for cerebellar atrophy. Given the fact that cerebellar atrophy is seen in other IGDs, flow cytometry for GPI-APs should be considered in the work-ups of individuals presenting this feature

M-CSF Induces Monocyte Survival by Activating NF-κB p65 Phosphorylation at Ser276 via Protein Kinase C

Macrophage colony-stimulating factor (M-CSF) promotes mononuclear phagocyte survival and proliferation. The transcription factor Nuclear Factor-kappaB (NF-κB) is a key regulator of genes involved in M-CSF-induced mononuclear phagocyte survival and this study focused at identifying the mechanism of NF-κB transcriptional activation. Here, we demonstrate that M-CSF stimulated NF-κB transcriptional activity in human monocyte-derived macrophages (MDMs) and the murine macrophage cell line RAW 264.7. The general protein kinase C (PKC) inhibitor Ro-31-8220, the conventional PKCα/β inhibitor Gö-6976, overexpression of dominant negative PKCα constructs and PKCα siRNA reduced NF-κB activity in response to M-CSF. Interestingly, Ro-31-8220 reduced Ser276 phosphorylation of NF-κBp65 leading to decreased M-CSF-induced monocyte survival. In this report, we identify conventional PKCs, including PKCα as important upstream kinases for M-CSF-induced NF-κB transcriptional activation, NF-κB-regulated gene expression, NF-κB p65 Ser276 phosphorylation, and macrophage survival. Lastly, we find that NF-κB p65 Ser276 plays an important role in basal and M-CSF-stimulated NF-κB activation in human mononuclear phagocytes

Observation of the Baryonic Flavor-Changing Neutral Current Decay Lambda_b -> Lambda mu+ mu-

We report the first observation of the baryonic flavor-changing neutral current decay Lambda_b -> Lambda mu+ mu- with 24 signal events and a statistical significance of 5.8 Gaussian standard deviations. This measurement uses ppbar collisions data sample corresponding to 6.8fb-1 at sqrt{s}=1.96TeV collected by the CDF II detector at the Tevatron collider. The total and differential branching ratios for Lambda_b -> Lambda mu+ mu- are measured. We find B(Lambda_b -> Lambda mu+ mu-) = [1.73+-0.42(stat)+-0.55(syst)] x 10^{-6}. We also report the first measurement of the differential branching ratio of B_s -> phi mu+ mu- using 49 signal events. In addition, we report branching ratios for B+ -> K+ mu+ mu-, B0 -> K0 mu+ mu-, and B -> K*(892) mu+ mu- decays.Comment: 8 pages, 2 figures, 4 tables. Submitted to Phys. Rev. Let

Evidence for t\bar{t}\gamma Production and Measurement of \sigma_t\bar{t}\gamma / \sigma_t\bar{t}

Using data corresponding to 6.0/fb of ppbar collisions at sqrt(s) = 1.96 TeV collected by the CDF II detector, we present a cross section measurement of top-quark pair production with an additional radiated photon. The events are selected by looking for a lepton, a photon, significant transverse momentum imbalance, large total transverse energy, and three or more jets, with at least one identified as containing a b quark. The ttbar+photon sample requires the photon to have 10 GeV or more of transverse energy, and to be in the central region. Using an event selection optimized for the ttbar+photon candidate sample we measure the production cross section of, and the ratio of cross sections of the two samples. Control samples in the dilepton+photon and lepton+photon+\met, channels are constructed to aid in decay product identification and background measurements. We observe 30 ttbar+photon candidate events compared to the standard model expectation of 26.9 +/- 3.4 events. We measure the ttbar+photon cross section to be 0.18+0.08 pb, and the ratio of the cross section of ttbar+photon to ttbar to be 0.024 +/- 0.009. Assuming no ttbar+photon production, we observe a probability of 0.0015 of the background events alone producing 30 events or more, corresponding to 3.0 standard deviations.Comment: 9 pages, 3 figure