Neutrophils alter epithelial response to Porphyromonas gingivalis in a gingival crevice model

A gingival crevice model (epithelial cell- Porphyromonas gingivalis – neutrophil) was established and used to profile gingipain, matrix metalloproteinase, MMP mediators (NGAL and TIMP-1) and cytokine networks. Smoking is the primary environmental risk factor for periodontitis. Therefore, the influence of cigarette smoke extract (CSE) was also monitored in the same model. P. gingivalis alone induced low levels of IL-1β and IL-8 from epithelial cells, but high levels of both cytokines were produced on the addition of neutrophils. CSE-exposure (100 and 1000 ng/ml nicotine equivalency) significantly compromised P. gingivalis-induced cytokine secretion (both p < 0.05). P. gingivalis induced impressive secretion of NGAL (p < 0.05) which was not influenced by CSE. The influence of CSE on gingipains production was strain-specific. Purified gingipains effectively and rapidly degraded both TIMP-1 and MMP-9. Induction of large amounts of NGAL, degradation of TIMP-1, and increased gingipain activity would each be expected to prolong collagen degradation and promote disease progression. However, gingipains also degrade MMP-9. Thus, P. gingivalis exerts a complex influence on the proteolytic balance of a gingival crevice model. CSE-exposure reduces the pro-inflammatory cytokine burden, which may be expected to promote P. gingivalis survival. In addition to novel findings that provide mechanistic insight into periodontal disease progression, these results are in keeping with the recognized clinical dogma of decreased inflammation / increased disease in smokers. Thus, this straightforward gingival crevice model is established as a suitable vehicle for the elucidation of mechanisms that contribute to susceptibility to periodontitis

Signatures of Spin and Charge Energy Scales in the Local Moment and Specific Heat of the Two-Dimensional Hubbard Model

Local moment formation driven by the on--site repulsion $U$ is one of the most fundamental features in the Hubbard model. At the simplest level, the temperature dependence of the local moment is expected to have a single structure at $T \sim U$, reflecting the suppression of the double occupancy. In this paper we show new low temperature Quantum Monte Carlo data which emphasize that the local moment also has a signature at a lower energy scale which previously had been thought to characterize only the temperatures below which moments on {\it different} sites begin to correlate locally. We discuss implications of these results for the structure of the specific heat, and connections to quasiparticle resonance and pseudogap formation in the density of states.Comment: 13 pages, 19 figure

Universality in Bacterial Colonies

The emergent spatial patterns generated by growing bacterial colonies have been the focus of intense study in physics during the last twenty years. Both experimental and theoretical investigations have made possible a clear qualitative picture of the different structures that such colonies can exhibit, depending on the medium on which they are growing. However, there are relatively few quantitative descriptions of these patterns. In this paper, we use a mechanistically detailed simulation framework to measure the scaling exponents associated with the advancing fronts of bacterial colonies on hard agar substrata, aiming to discern the universality class to which the system belongs. We show that the universal behavior exhibited by the colonies can be much richer than previously reported, and we propose the possibility of up to four different sub-phases within the medium-to-high nutrient concentration regime. We hypothesize that the quenched disorder that characterizes one of these sub-phases is an emergent property of the growth and division of bacteria competing for limited space and nutrients.Comment: 12 pages, 5 figure

Integrated analysis of RNA and DNA from the phase III trial CALGB 40601 identifies predictors of response to trastuzumab-based neoadjuvant chemotherapy in HER2-positive breast cancer

Purpose: Response to a complex trastuzumab-based regimen is affected by multiple features of the tumor and its microenvironment. Developing a predictive algorithm is key to optimizing HER2-targeting therapy. Experimental Design: We analyzed 137 pretreatment tumors with mRNA-seq and DNA exome sequencing from CALGB 40601, a neoadjuvant phase III trial of paclitaxel plus trastuzumab with or without lapatinib in stage II to III HER2-positive breast cancer. We adopted an Elastic Net regularized regression approach that controls for covarying features within high-dimensional data. First, we applied 517 known gene expression signatures to develop an Elastic Net model to predict pCR, which we validated on 143 samples from four independent trials. Next, we performed integrative analyses incorporating clinicopathologic information with somatic mutation status, DNA copy number alterations (CNA), and gene signatures. Results: The Elastic Net model using only gene signatures predicted pCR in the validation sets (AUC ¼ 0.76). Integrative analyses showed that models containing gene signatures, clinical features, and DNA information were better pCR predictors than models containing a single data type. Frequently selected variables from the multiplatform models included amplifications of chromosome 6p, TP53 mutation, HER2-enriched subtype, and immune signatures. Variables predicting resistance included Luminal/ERþ features. Conclusions: Models using RNA only, as well as integrated RNA and DNA models, can predict pCR with improved accuracy over clinical variables. Somatic DNA alterations (mutation, CNAs), tumor molecular subtype (HER2E, Luminal), and the microenvironment (immune cells) were independent predictors of response to trastuzumab and paclitaxel-based regimens. This highlights the complexity of predicting response in HER2-positive breast cancer

Implementation of mandatory opioid prescribing limits in North Carolina: healthcare administrator and prescriber perspectives

Background: Recent increases in state laws to reduce opioid prescribing have demonstrated a need to understand how they are interpreted and implemented in healthcare systems. The purpose of this study was to explore the systems, strategies, and resources that hospital administrators and prescribers used to implement the 2017 North Carolina Strengthen Opioid Prevention (STOP) Act opioid prescribing limits, which limited initial prescriptions to a five (for acute) or seven (for post-surgical) days’ supply. Methods: We interviewed 14 hospital administrators and 38 prescribers with degrees in medicine, nursing, pharmacy, business administration and public health working across North Carolina. Interview guides, informed by the Consolidated Framework for Implementation Research, explored barriers and facilitators to implementation. Interview topics included communication, resources, and hospital system support. Interviews were recorded and transcribed, then analyzed using flexible coding, integrating inductive and deductive coding, to inform analytic code development and identify themes. Results: We identified three main themes around implementation of STOP act mandated prescribing limits: organizational communication, prescriber education, and changes in the electronic medical record (EMR) systems. Administrators reflected on implementation in the context of raising awareness and providing reminders to facilitate changes in prescriber behavior, operationalized through email and in-person communications as well as dedicated resources to EMR changes. Prescribers noted administrative communications about prescribing limits often focused on legality, suggesting a directive of the organization’s policy rather than a passive reminder. Prescribers expressed a desire for more spaces to have their questions answered and resources for patient communications. While hospital administrators viewed compliance with the law as a priority, prescribers reflected on concerns for adequately managing their patients’ pain and limited time for clinical care. Conclusions: Hospital administrators and prescribers approached implementation of the STOP act prescribing limits with different mindsets. While administrators were focused on policy compliance, prescribers were focused on their patients’ needs. Strategies to implement the mandate then had to balance patient needs with policy compliance. As states continue to legislate to prevent opioid overdose deaths, understanding how laws are implemented by healthcare systems and prescribers will improve their effectiveness through tailoring and maximizing available resources

Database Programming in Machiavelli - a Polymorphic Language with Static Type Inference

Machiavelli is a polymorphically typed programming language in the spirit of ML, but supports an extended method of type inferencing that makes its polymorphism more general and appropriate for database applications. In particular, a function that selects a field f of a records is polymorphic in the sense that it can be applied to any record which contains a field f with the appropriate type. When combined with a set data type and database operations including join and projection, this provides a natural medium for relational database programming. Moreover, by implementing database objects as reference types and generating the appropriate views — sets of structures with “identity ” — we can achieve a degree of static type checking for object-oriented databases.

The Science of Sungrazers, Sunskirters, and Other Near-Sun Comets

This review addresses our current understanding of comets that venture close to the Sun, and are hence exposed to much more extreme conditions than comets that are typically studied from Earth. The extreme solar heating and plasma environments that these objects encounter change many aspects of their behaviour, thus yielding valuable information on both the comets themselves that complements other data we have on primitive solar system bodies, as well as on the near-solar environment which they traverse. We propose clear definitions for these comets: We use the term near-Sun comets to encompass all objects that pass sunward of the perihelion distance of planet Mercury (0.307 AU). Sunskirters are defined as objects that pass within 33 solar radii of the Sun’s centre, equal to half of Mercury’s perihelion distance, and the commonly-used phrase sungrazers to be objects that reach perihelion within 3.45 solar radii, i.e. the fluid Roche limit. Finally, comets with orbits that intersect the solar photosphere are termed sundivers. We summarize past studies of these objects, as well as the instruments and facilities used to study them, including space-based platforms that have led to a recent revolution in the quantity and quality of relevant observations. Relevant comet populations are described, including the Kreutz, Marsden, Kracht, and Meyer groups, near-Sun asteroids, and a brief discussion of their origins. The importance of light curves and the clues they provide on cometary composition are emphasized, together with what information has been gleaned about nucleus parameters, including the sizes and masses of objects and their families, and their tensile strengths. The physical processes occurring at these objects are considered in some detail, including the disruption of nuclei, sublimation, and ionisation, and we consider the mass, momentum, and energy loss of comets in the corona and those that venture to lower altitudes. The different components of comae and tails are described, including dust, neutral and ionised gases, their chemical reactions, and their contributions to the near-Sun environment. Comet-solar wind interactions are discussed, including the use of comets as probes of solar wind and coronal conditions in their vicinities. We address the relevance of work on comets near the Sun to similar objects orbiting other stars, and conclude with a discussion of future directions for the field and the planned ground- and space-based facilities that will allow us to address those science topics

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Seven-year follow-up analysis of adjuvant paclitaxel and trastuzumab trial for node-negative, human epidermal growth factor receptor 2–positive breast cancer

PURPOSE The Adjuvant Paclitaxel and Trastuzumab trial was designed to address treatment of patients with small human epidermal growth factor receptor 2 (HER2)–positive breast cancer. The primary analysis of the Adjuvant Paclitaxel and Trastuzumab trial demonstrated a 3-year disease-free survival (DFS) of 98.7%. In this planned secondary analysis, we report longer-term outcomes and exploratory results to characterize the biology of small HER2-positive tumors and genetic factors that may predispose to paclitaxel-induced peripheral neuropathy (TIPN). PATIENTS AND METHODS In this phase II study, patients with HER2-positive breast cancer with tumors 3 cm or smaller and negative nodes received paclitaxel (80 mg/m2) with trastuzumab for 12 weeks, followed by trastuzumab for 9 months. The primary end point was DFS. Recurrence-free interval (RFI), breast cancer–specific survival, and overall survival (OS) were also analyzed. In an exploratory analysis, intrinsic subtyping by PAM50 (Prosigna) and calculation of the risk of recurrence score were performed on the nCounter analysis system on archival tissue. Genotyping was performed to investigate TIPN. RESULTS A total of 410 patients were enrolled from October 2007 to September 2010. After a median follow-up of 6.5 years, there were 23 DFS events. The 7-year DFS was 93% (95% CI, 90.4 to 96.2) with four (1.0%) distant recurrences, 7-year OS was 95% (95% CI, 92.4 to 97.7), and 7-year RFI was 97.5% (95% CI, 95.9 to 99.1). PAM50 analyses (n = 278) showed that most tumors were HER2-enriched (66%), followed by luminal B (14%), luminal A (13%), and basal-like (8%). Genotyping (n = 230) identified one single-nucleotide polymorphism, rs3012437, associated with an increased risk of TIPN in patients with grade 2 or greater TIPN (10.4%). CONCLUSION With longer follow-up, adjuvant paclitaxel and trastuzumab is associated with excellent long-term outcomes. Distribution of PAM50 intrinsic subtypes in small HER2-positive tumors is similar to that previously reported for larger tumors