Correlation of X-ray diffraction signatures of breast tissue and their histopathological classification

This pilot study examines the correlation of X-ray diffraction (XRD) measurements with the histopathological analysis of breast tissue. Eight breast cancer samples were investigated. Each sample contained a mixture of normal and cancerous tissues. In total, 522 separate XRD measurements were made at different locations across the samples (8 in total). The resulting XRD spectra were subjected to principal component analysis (PCA) in order to determine if there were any distinguishing features that could be used to identify different tissue components. 99.0% of the variation between the spectra were described by the first two principal components (PC). Comparing the location of points in PC space with the classification determined by histopathology indicated correlation between the shape/magnitude of the XRD spectra and the tissue type. These results are encouraging and suggest that XRD could be used for the intraoperative or postoperative classification of bulk tissue samples

Towards a characterization of behavior-disease models

The last decade saw the advent of increasingly realistic epidemic models that leverage on the availability of highly detailed census and human mobility data. Data-driven models aim at a granularity down to the level of households or single individuals. However, relatively little systematic work has been done to provide coupled behavior-disease models able to close the feedback loop between behavioral changes triggered in the population by an individual's perception of the disease spread and the actual disease spread itself. While models lacking this coupling can be extremely successful in mild epidemics, they obviously will be of limited use in situations where social disruption or behavioral alterations are induced in the population by knowledge of the disease. Here we propose a characterization of a set of prototypical mechanisms for self-initiated social distancing induced by local and non-local prevalence-based information available to individuals in the population. We characterize the effects of these mechanisms in the framework of a compartmental scheme that enlarges the basic SIR model by considering separate behavioral classes within the population. The transition of individuals in/out of behavioral classes is coupled with the spreading of the disease and provides a rich phase space with multiple epidemic peaks and tipping points. The class of models presented here can be used in the case of data-driven computational approaches to analyze scenarios of social adaptation and behavioral change.Comment: 24 pages, 15 figure

Untangling the Interplay between Epidemic Spread and Transmission Network Dynamics

The epidemic spread of infectious diseases is ubiquitous and often has a considerable impact on public health and economic wealth. The large variability in the spatio-temporal patterns of epidemics prohibits simple interventions and requires a detailed analysis of each epidemic with respect to its infectious agent and the corresponding routes of transmission. To facilitate this analysis, we introduce a mathematical framework which links epidemic patterns to the topology and dynamics of the underlying transmission network. The evolution, both in disease prevalence and transmission network topology, is derived from a closed set of partial differential equations for infections without allowing for recovery. The predictions are in excellent agreement with complementarily conducted agent-based simulations. The capacity of this new method is demonstrated in several case studies on HIV epidemics in synthetic populations: it allows us to monitor the evolution of contact behavior among healthy and infected individuals and the contributions of different disease stages to the spreading of the epidemic. This gives both direction to and a test bed for targeted intervention strategies for epidemic control. In conclusion, this mathematical framework provides a capable toolbox for the analysis of epidemics from first principles. This allows for fast, in silico modeling - and manipulation - of epidemics and is especially powerful if complemented with adequate empirical data for parameterization

Age-prioritized use of antivirals during an influenza pandemic

<p>Abstract</p> <p>Background</p> <p>The WHO suggested that governments stockpile, as part of preparations for the next influenza pandemic, sufficient influenza antiviral drugs to treat approximately 25% of their populations. Our aim is two-fold: first, since in many countries the antiviral stockpile is well below this level, we search for suboptimal strategies based on treatment provided only to an age-dependent fraction of cases. Second, since in some countries the stockpile exceeds the suggested minimum level, we search for optimal strategies for post-exposure prophylactic treatment of close contacts of cases.</p> <p>Methods</p> <p>We used a stochastic, spatially structured individual-based model, considering explicit transmission in households, schools and workplaces, to simulate the spatiotemporal spread of an influenza pandemic in Italy and to evaluate the efficacy of interventions based on age-prioritized use of antivirals.</p> <p>Results</p> <p>Our results show that the antiviral stockpile required for treatment of cases ranges from 10% to 35% of the population for <it>R</it>₀in 1.4 – 3. No suboptimal strategies, based on treatment provided to an age-dependent fraction of cases, were found able to remarkably reduce both clinical attack rate and antiviral drugs needs, though they can contribute to largely reduce the excess mortality. Treatment of all cases coupled with prophylaxis provided to younger individuals is the only intervention resulting in a significant reduction of the clinical attack rate and requiring a relatively small stockpile of antivirals.</p> <p>Conclusion</p> <p>Our results strongly suggest that governments stockpile sufficient influenza antiviral drugs to treat approximately 25% of their populations, under the assumption that <it>R</it>₀is not much larger than 2. In countries where the number of antiviral stockpiled exceeds the suggested minimum level, providing prophylaxis to younger individuals is an option that could be taken into account in preparedness plans. In countries where the number of antivirals stockpiled is well below 25% of the population, priority should be decided based on age-specific case fatality rates. However, late detection of cases (administration of antivirals 48 hours after the clinical onset of symptoms) dramatically affects the efficacy of both treatment and prophylaxis.</p

Current Treatment of Endolymphatic Sac Tumor of the Temporal Bone

An endolymphatic sac tumor (ELST) is a rare, indolent but locally aggressive tumor arising in the posterior petrous ridge. Patients present with sensorineural hearing loss and tinnitus. As the tumor progresses, patients may experience vertigo, ataxia, facial nerve paresis, pain and otorrhea. Most patients present in their 4th or 5th decade with a wide age range. Patients with von Hippel–Lindau disease have an increased likelihood of developing ELST. Histologically, ELST is a low-grade adenocarcinoma. As it progresses, it destroys bone and extends into adjacent tissues. The likelihood of regional or distant metastases is remote. The optimal treatment is resection with negative margins. Patients with positive margins, gross residual disease, or unresectable tumor are treated with radiotherapy or radiosurgery. Late recurrences are common, so long follow-up is necessary to assess efficacy. The likelihood of cure depends on tumor extent and is probably in the range of 50–75%

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Detection and Early Referral of Patients With Interstitial Lung Abnormalities: An Expert Survey Initiative

Background: Interstitial lung abnormalities (ILA) may represent undiagnosed early-stage or subclinical interstitial lung disease (ILD). ILA are often observed incidentally in patients who subsequently develop clinically overt ILD. There is limited information on consensus definitions for, and the appropriate evaluation of, ILA. Early recognition of patients with ILD remains challenging, yet critically important. Expert consensus could inform early recognition and referral. Research Question: Can consensus-based expert recommendations be identified to guide clinicians in the recognition, referral, and follow-up of patients with or at risk of developing early ILDs? Study Design and Methods: Pulmonologists and radiologists with expertise in ILD participated in two iterative rounds of surveys. The surveys aimed to establish consensus regarding ILA reporting, identification of patients with ILA, and identification of populations that might benefit from screening for ILD. Recommended referral criteria and follow-up processes were also addressed. Threshold for consensus was defined a priori as ≥ 75% agreement or disagreement. Results: Fifty-five experts were invited and 44 participated; consensus was reached on 39 of 85 questions. The following clinically important statements achieved consensus: honeycombing and traction bronchiectasis or bronchiolectasis indicate potentially progressive ILD; honeycombing detected during lung cancer screening should be reported as potentially significant (eg, with the Lung CT Screening Reporting and Data System “S-modifier” [Lung-RADS; which indicates clinically significant or potentially significant noncancer findings]), recommending referral to a pulmonologist in the radiology report; high-resolution CT imaging and full pulmonary function tests should be ordered if nondependent subpleural reticulation, traction bronchiectasis, honeycombing, centrilobular ground-glass nodules, or patchy ground-glass opacity are observed on CT imaging; patients with honeycombing or traction bronchiectasis should be referred to a pulmonologist irrespective of diffusion capacity values; and patients with systemic sclerosis should be screened with pulmonary function tests for early-stage ILD. Interpretation: Guidance was established for identifying clinically relevant ILA, subsequent referral, and follow-up. These results lay the foundation for developing practical guidance on managing patients with ILA

High power Q-switched thulium doped fibre laser using carbon nanotube polymer composite saturable absorber

We have proposed and demonstrated a Q-switched Thulium doped bre laser (TDFL) with a ‘Yin-Yang’ all- bre cavity scheme based on a combination of nonlinear optical loop mirror (NOLM) and nonlinear ampli ed loop mirror (NALM). Unidirectional lasing operation has been achieved without any intracavity isolator. By using a carbon nanotube polymer composite based saturable absorber (SA), we demonstrated the laser output power of ~197 mW and pulse energy of 1.7 μJ. To the best of our knowledge, this is the highest output power from a nanotube polymer composite SA based Q-switched Thulium doped bre laser

Inhibition of autophagy, lysosome and VCP function impairs stress granule assembly

Stress granules (SGs) are mRNA-protein aggregates induced during stress, which accumulate in many neurodegenerative diseases. Previously, the autophagy-lysosome pathway and valosin-containing protein (VCP), key players of the protein quality control (PQC), were shown to regulate SG degradation. This is consistent with the idea that PQC may survey and/or assist SG dynamics. However, despite these observations, it is currently unknown whether the PQC actively participates in SG assembly. Here, we describe that inhibition of autophagy, lysosomes and VCP causes defective SG formation after induction. Silencing the VCP co-factors UFD1L and PLAA, which degrade defective ribosomal products (DRIPs) and 60S ribosomes, also impaired SG assembly. Intriguingly, DRIPs and 60S, which are released from disassembling polysomes and are normally excluded from SGs, were significantly retained within SGs in cells with impaired autophagy, lysosome or VCP function. Our results suggest that deregulated autophagy, lysosomal or VCP activities, which occur in several neurodegenerative (VCP-associated) diseases, may alter SG morphology and composition