Development of a Web-based Resident Profiling Tool to Support Training in Practice-based Learning and Improvement

Multiple factors are driving residency programs to explicitly address practice-based learning and improvement (PBLI), yet few information systems exist to facilitate such training. We developed, implemented, and evaluated a Web-based tool that provides Internal Medicine residents at the University of Virginia Health System with population-based reports about their ambulatory clinical experiences. Residents use Systems and Practice Analysis for Resident Competencies (SPARC) to identify potential areas for practice improvement. Thirty-three (65%) of 51 residents completed a survey assessing SPARC’s usefulness, with 94% agreeing that it was a useful educational tool. Twenty-six residents (51%) completed a before–after study indicating increased agreement (5-point Likert scale, with 5=strongly agree) with statements regarding confidence in ability to access population-based data about chronic disease management (mean [SD] 2.5 [1.2] vs. 4.5 [0.5], p < .001, sign test) and information comparing their practice style to that of their peers (2.2 [1.2] vs. 4.6 [0.5], p < .001)

Presumed small vessel disease, imaging and cognition markers in the Alzheimer's Disease Neuroimaging Initiative

MRI-derived features of presumed cerebral small vessel disease are frequently found in Alzheimer’s disease. Influences of such markers on disease-progression measures are poorly understood. We measured markers of presumed small vessel disease (white matter hyperintensity volumes; cerebral microbleeds) on baseline images of newly enrolled individuals in the Alzheimer’s Disease Neuroimaging Initiative cohort (GO and 2) and used linear mixed models to relate these to subsequent atrophy and neuropsychological score change. We also assessed heterogeneity in white matter hyperintensity positioning within biomarker abnormality sequences, driven by the data, using the Subtype and Stage Inference algorithm. This study recruited both sexes and included: controls: [n = 159, mean(SD) age = 74(6) years]; early and late mild cognitive impairment [ns = 265 and 139, respectively, mean(SD) ages =71(7) and 72(8) years, respectively]; Alzheimer’s disease [n = 103, mean(SD) age = 75(8)] and significant memory concern [n = 72, mean(SD) age = 72(6) years]. Baseline demographic and vascular risk-factor data, and longitudinal cognitive scores (Mini-Mental State Examination; logical memory; and Trails A and B) were collected. Whole-brain and hippocampal volume change metrics were calculated. White matter hyperintensity volumes were associated with greater whole-brain and hippocampal volume changes independently of cerebral microbleeds (a doubling of baseline white matter hyperintensity was associated with an increase in atrophy rate of 0.3 ml/year for brain and 0.013 ml/year for hippocampus). Cerebral microbleeds were found in 15% of individuals and the presence of a microbleed, as opposed to none, was associated with increases in atrophy rate of 1.4 ml/year for whole brain and 0.021 ml/year for hippocampus. White matter hyperintensities were predictive of greater decline in all neuropsychological scores, while cerebral microbleeds were predictive of decline in logical memory (immediate recall) and Mini-Mental State Examination scores. We identified distinct groups with specific sequences of biomarker abnormality using continuous baseline measures and brain volume change. Four clusters were found; Group 1 showed early Alzheimer’s pathology; Group 2 showed early neurodegeneration; Group 3 had early mixed Alzheimer’s and cerebrovascular pathology; Group 4 had early neuropsychological score abnormalities. White matter hyperintensity volumes becoming abnormal was a late event for Groups 1 and 4 and an early event for 2 and 3. In summary, white matter hyperintensities and microbleeds were independently associated with progressive neurodegeneration (brain atrophy rates) and cognitive decline (change in neuropsychological scores). Mechanisms involving white matter hyperintensities and progression and microbleeds and progression may be partially separate. Distinct sequences of biomarker progression were found. White matter hyperintensity development was an early event in two sequences

Identifying Critical Non-Catalytic Residues that Modulate Protein Kinase A Activity

Distal interactions between discrete elements of an enzyme are critical for communication and ultimately for regulation. However, identifying the components of such interactions has remained elusive due to the delicate nature of these contacts. Protein kinases are a prime example of an enzyme with multiple regulatory sites that are spatially separate, yet communicate extensively for tight regulation of activity. Kinase misregulation has been directly linked to a variety of cancers, underscoring the necessity for understanding intramolecular kinase regulation.A genetic screen was developed to identify suppressor mutations that restored catalytic activity in vivo from two kinase-dead Protein Kinase A mutants in S. cerevisiae. The residues defined by the suppressors provide new insights into kinase regulation. Many of the acquired mutations were distal to the nucleotide binding pocket, highlighting the relationship of spatially dispersed residues in regulation.The suppressor residues provide new insights into kinase regulation, including allosteric effects on catalytic elements and altered protein-protein interactions. The suppressor mutations identified in this study also share overlap with mutations identified from an identical screen in the yeast PKA homolog Tpk2, demonstrating functional conservation for some residues. Some mutations were independently isolated several times at the same sites. These sites are in agreement with sites previously identified from multiple cancer data sets as areas where acquired somatic mutations led to cancer progression and drug resistance. This method provides a valuable tool for identifying residues involved in kinase activity and for studying kinase misregulation in disease states

Preventive drugs in the last year of life of older adults with cancer: Is there room for deprescribing?

BACKGROUND: The continuation of preventive drugs among older patients with advanced cancer has come under scrutiny because these drugs are unlikely to achieve their clinical benefit during the patients' remaining lifespan. METHODS: A nationwide cohort study of older adults (those aged ≥65 years) with solid tumors who died between 2007 and 2013 was performed in Sweden, using routinely collected data with record linkage. The authors calculated the monthly use and cost of preventive drugs throughout the last year before the patients' death. RESULTS: Among 151,201 older persons who died with cancer (mean age, 81.3 years [standard deviation, 8.1 years]), the average number of drugs increased from 6.9 to 10.1 over the course of the last year before death. Preventive drugs frequently were continued until the final month of life, including antihypertensives, platelet aggregation inhibitors, anticoagulants, statins, and oral antidiabetics. Median drug costs amounted to $1482 (interquartile range [IQR],$700-$2896]) per person, including$213 (IQR, $77-$490) for preventive therapies. Compared with older adults who died with lung cancer (median drug cost, $205; IQR,$61-$523), costs for preventive drugs were higher among older adults who died with pancreatic cancer (adjusted median difference,$13; 95% confidence interval, $5-$22) or gynecological cancers (adjusted median difference, $27; 95$18-$36). There was no decrease noted with regard to the cost of preventive drugs throughout the last year of life. CONCLUSIONS: Preventive drugs commonly are prescribed during the last year of life among older adults with cancer, and often are continued until the final weeks before death. Adequate deprescribing strategies are warranted to reduce the burden of drugs with limited clinical benefit near the end of life

Standardization of epidemiological surveillance of invasive Group A streptococcal infections

Invasive group A streptococcal (Strep A) infections occur when Streptococcus pyogenes, also known as beta-hemolytic group A Streptococcus, invades a normally sterile site in the body. This article provides guidelines for establishing surveillance for invasive Strep A infections. The primary objective of invasive Strep A surveillance is to monitor trends in rates of infection and determine the demographic and clinical characteristics of patients with laboratory-confirmed invasive Strep A infection, the age- and sex-specific incidence in the population of a defined geographic area, trends in risk factors, and the mortality rates and rates of nonfatal sequelae caused by invasive Strep A infections. This article includes clinical descriptions followed by case definitions, based on clinical and laboratory evidence, and case classifications (confirmed or probable, if applicable) for invasive Strep A infections and for 3 Strep A syndromes: streptococcal toxic shock syndrome, necrotizing fasciitis, and pregnancy-associated Strep A infection. Considerations of the type of surveillance are also presented, noting that most people who have invasive Strep A infections will present to hospital and that invasive Strep A is a notifiable disease in some countries. Minimal surveillance necessary for invasive Strep A infection is facility-based, passive surveillance. A resource-intensive but more informative approach is active case finding of laboratory-confirmed Strep A invasive infections among a large (eg, state-wide) and well defined population. Participant eligibility, surveillance population, and additional surveillance components such as the use of International Classification of Disease diagnosis codes, follow-up, period of surveillance, seasonality, and sample size are discussed. Finally, the core data elements to be collected on case report forms are presented

Study of Bc+B_c^+ decays to the K+K−π+K^+K^-\pi^+ final state and evidence for the decay Bc+→χc0π+B_c^+\to\chi_{c0}\pi^+

A study of $B_c^+\to K^+K^-\pi^+$ decays is performed for the first time using data corresponding to an integrated luminosity of 3.0 $\mathrm{fb}^{-1}$ collected by the LHCb experiment in $pp$ collisions at centre-of-mass energies of $7$ and $8$ TeV. Evidence for the decay $B_c^+\to\chi_{c0}(\to K^+K^-)\pi^+$ is reported with a significance of 4.0 standard deviations, resulting in the measurement of $\frac{\sigma(B_c^+)}{\sigma(B^+)}\times\mathcal{B}(B_c^+\to\chi_{c0}\pi^+)$ to be $(9.8^{+3.4}_{-3.0}(\mathrm{stat})\pm 0.8(\mathrm{syst}))\times 10^{-6}$. Here $\mathcal{B}$ denotes a branching fraction while $\sigma(B_c^+)$ and $\sigma(B^+)$ are the production cross-sections for $B_c^+$ and $B^+$ mesons. An indication of $\bar b c$ weak annihilation is found for the region $m(K^-\pi^+)<1.834\mathrm{\,Ge\kern -0.1em V\!/}c^2$, with a significance of 2.4 standard deviations.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2016-022.html, link to supplemental material inserted in the reference

E2F1 Regulates Cellular Growth by mTORC1 Signaling

During cell proliferation, growth must occur to maintain homeostatic cell size. Here we show that E2F1 is capable of inducing growth by regulating mTORC1 activity. The activation of cell growth and mTORC1 by E2F1 is dependent on both E2F1's ability to bind DNA and to regulate gene transcription, demonstrating that a gene induction expression program is required in this process. Unlike E2F1, E2F3 is unable to activate mTORC1, suggesting that growth activity could be restricted to individual E2F members. The effect of E2F1 on the activation of mTORC1 does not depend on Akt. Furthermore, over-expression of TSC2 does not interfere with the effect of E2F1, indicating that the E2F1-induced signal pathway can compensate for the inhibitory effect of TSC2 on Rheb. Immunolocalization studies demonstrate that E2F1 induces the translocation of mTORC1 to the late endosome vesicles, in a mechanism dependent of leucine. E2F1 and leucine, or insulin, together affect the activation of S6K stronger than alone suggesting that they are complementary in activating the signal pathway. From these studies, E2F1 emerges as a key protein that integrates cell division and growth, both of which are essential for cell proliferation