Full-length TrkB variant in NSCLC is associated with brain metastasis

Despite remarkable therapeutic advances have been made in the last few decades, non-small cell lung cancer (NSCLC) is still one of the leading causes of death worldwide. Brain metastases are a common complication of a wide range of human malignancies and in particular NSCLC. Brain-derived neurotrophic factor (BDNF), binding its high-affinity tyrosine kinase B receptor, has been shown to promote cancer progression and metastasis. We hereby investigated the expression of the BDNF and its TrkB receptor in its full-length and truncated isoform T1, in samples from primary adenocarcinomas (ADKs) of the lung and in their metastasis to evaluate if their expression was related to preferential tumor entry into the central nervous system (CNS). By immunohistochemistry, 80% of the ADKs that metastasize to central nervous system expressed TrkB receptor compared to 33% expressing of ADKs without CNS metastasis. Moreover, ADKs with CNS metastasis showed an elevated expression of the full-length TrkB receptor. The TrkB receptor FL/T1 ratio was statistically higher in primary ADKs with brain metastasis compared to ADKs without brain metastasis. Our data indicate that TrkB full-length isoform expression in primary ADK cells may be associated with higher risk to develop brain metastasis. Therefore, TrkB receptor may possess prognostic and therapeutic implications in lung ADK

Cost-effectiveness of next-generation vaccines: The case of pertussis.

Despite steady vaccination coverage rates, pertussis incidence in the United States has continued to rise. This public health challenge has motivated calls for the development of a new vaccine with greater efficacy and duration of protection. Any next-generation vaccine would likely come at a higher cost, and must provide sufficient health benefits beyond those provided by the current vaccine in order to be deemed cost-effective. Using an age-structured transmission model of pertussis, we quantified the health and economic benefits of a next-generation vaccine that would enhance either the efficacy or duration of protection of the childhood series, the duration of the adult booster, or a combination. We developed a metric, the maximum cost-effective price increase (MCPI), to compare the potential value of such improvements. The MCPI estimates the per-dose price increase that would maintain the cost-effectiveness of pertussis vaccination. We evaluated the MCPI across a range of potential single and combined improvements to the pertussis vaccine. As an upper bound, we found that a next-generation vaccine which could achieve perfect efficacy for the childhood series would permit an MCPI of $18 per dose (95$12-$31). Pertussis vaccine improvements that extend the duration of protection to an average of 75 years would allow for an MCPI of$22 per dose for the childhood series (CI: $10-$33) or $12 for the adult booster (CI:$4-$18). Despite the short duration of the adult booster, improvements to the childhood series could be more valuable than improvements to the adult booster. Combining improvements in both efficacy and duration, a childhood series with perfect efficacy and average duration of 75 years would permit an MCPI of$39 per dose, the highest of any scenario evaluated. Our results highlight the utility of the MCPI metric in evaluating potential vaccines or other interventions when prices are unknown

Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge

Background: Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013-14 Unites States influenza season. Methods: Challenge contestants were asked to forecast the start, peak, and intensity of the 2013-2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013-March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results: Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion: Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts. © 2016 The Author(s)

Using combined diagnostic test results to hindcast trends of infection from cross-sectional data

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to ‘hindcast’ (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time

Crowding and the shape of COVID-19 epidemics

The coronavirus disease 2019 (COVID-19) pandemic is straining public health systems worldwide, and major non-pharmaceutical interventions have been implemented to slow its spread1,2,3,4. During the initial phase of the outbreak, dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was primarily determined by human mobility from Wuhan, China5,6. Yet empirical evidence on the effect of key geographic factors on local epidemic transmission is lacking7. In this study, we analyzed highly resolved spatial variables in cities, together with case count data, to investigate the role of climate, urbanization and variation in interventions. We show that the degree to which cases of COVID-19 are compressed into a short period of time (peakedness of the epidemic) is strongly shaped by population aggregation and heterogeneity, such that epidemics in crowded cities are more spread over time, and crowded cities have larger total attack rates than less populated cities. Observed differences in the peakedness of epidemics are consistent with a meta-population model of COVID-19 that explicitly accounts for spatial hierarchies. We paired our estimates with globally comprehensive data on human mobility and predict that crowded cities worldwide could experience more prolonged epidemics

Activated Leukocyte Cell Adhesion Molecule Expression and Shedding in Thyroid Tumors

Activated leukocyte cell adhesion molecule (ALCAM, CD166) is expressed in various tissues, cancers, and cancer-initiating cells. Alterations in expression of ALCAM have been reported in several human tumors, and cell adhesion functions have been proposed to explain its association with cancer. Here we documented high levels of ALCAM expression in human thyroid tumors and cell lines. Through proteomic characterization of ALCAM expression in the human papillary thyroid carcinoma cell line TPC-1, we identified the presence of a full-length membrane-associated isoform in cell lysate and of soluble ALCAM isoforms in conditioned medium. This finding is consistent with proteolytically shed ALCAM ectodomains. Nonspecific agents, such as phorbol myristate acetate (PMA) or ionomycin, provoked increased ectodomain shedding. Epidermal growth factor receptor stimulation also enhanced ALCAM secretion through an ADAM17/TACE-dependent pathway. ADAM17/TACE was expressed in the TPC-1 cell line, and ADAM17/TACE silencing by specific small interfering RNAs reduced ALCAM shedding. In addition, the CGS27023A inhibitor of ADAM17/TACE function reduced ALCAM release in a dose-dependent manner and inhibited cell migration in a wound-healing assay. We also provide evidence for the existence of novel O-glycosylated forms and of a novel 60-kDa soluble form of ALCAM, which is particularly abundant following cell stimulation by PMA. ALCAM expression in papillary and medullary thyroid cancer specimens and in the surrounding non-tumoral component was studied by western blot and immunohistochemistry, with results demonstrating that tumor cells overexpress ALCAM. These findings strongly suggest the possibility that ALCAM may have an important role in thyroid tumor biology

Sampling bias and incorrect rooting make phylogenetic network tracing of SARS-COV-2 infections unreliable.

There is obvious interest in gaining insights into the epidemiology and evolution of the virus that has recently emerged in humans as the cause of the coronavirus disease 2019 (COVID-19) pandemic. The recent paper by Forster et al. (1), analyzed 160 SARS-CoV-2 full genomes available (https://www.gisaid.org/) in early March 2020. The central claim is the identification of three main SARS-CoV-2 types, named A, B, and C, circulating in different proportions among Europeans and Americans (types A and C) and East Asian (type B). According to a median-joining network analysis, variant A is proposed to be the ancestral type because it links to the sequence of a coronavirus from bats, used as an outgroup to trace the ancestral origin of the human strains. The authors further suggest that the “ancestral Wuhan B-type virus is immunologically or environmentally adapted to a large section of the East Asian population, and may need to mutate to overcome resistance outside East Asia”. There are several serious flaws with their findings and interpretation. First, and most obviously, the sequence identity between SARS-CoV-2 and the bat virus is only 96.2%, implying that these viral genomes (which are nearly 30,000 nucleotides long) differ by more than 1,000 mutations. Such a distant outgroup is unlikely to provide a reliable root for the network. Yet, strangely, the branch to the bat virus, in Figure 1 of the paper, is only 16 or 17 mutations in length. Indeed, the network seems to be mis-rooted because (see Supplementary Figure 4) a virus from Wuhan from week 0 (24th December 2019) is portrayed as a descendant of a clade of viruses collected in weeks 1-9 (presumably from many places outside China), which makes no evolutionary (2), nor epidemiological sense (3).N

Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications

Damien Caillaud is with UT Austin and Max Planck Institute for Evolutionary Anthropology; Margaret C. Crofoot is with the Smithsonian Tropical Research Institute, Max Planck Institute for Ornithology, and Princeton University; Samuel V. Scarpino is with UT Austin; Patrick A. Jansen is with the Smithsonian Tropical Research Institute, Wageningen University, and University of Groningen; Carol X. Garzon-Lopez is with University of Groningen; Annemarie J. S. Winkelhagen is with Wageningen University; Stephanie A. Bohlman is with Princeton University; Peter D. Walsh is with VaccinApe.Background -- The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings -- Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance -- We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI.The National Center For Ecological Analysis is supported by NSF Grant DEB-0553768, the University of California Santa Barbara and the State of California. The Forest Dynamics Plots were funded by NSF Grants to Stephen Hubbell DEB-0640386, DEB-0425651, DEB-0346488, DEB-0129874, DEB-00753102, DEB-9909347, DEB-9615226, DEB-9615226, DEB-9405933, DEB-9221033, DEB-9100058, DEB-8906869, DEB-8605042, DEB-8206992, DEB-7922197, and by the Center for Tropical Forest Science, the Smithsonian Tropical Forest Research Institute, The John D. and Catherine T. MacArthur Foundation, the Mellon Foundation and the Celera Foundation. DC is supported by NSF grant DEB-0749097 to L.A. Meyers. SS is supported by an NSF Graduate Research Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Biological Sciences, School o

Relationship between low Ankle-Brachial Index and rapid renal function decline in patients with atrial fibrillation: A prospective multicentre cohort study

OBJECTIVE: To investigate the relationship between Ankle-Brachial Index (ABI) and renal function progression in patients with atrial fibrillation (AF). DESIGN: Observational prospective multicentre cohort study. SETTING:Atherothrombosis Center of I Clinica Medica of 'Sapienza' University of Rome; Department of Medical and Surgical Sciences of University Magna Græcia of Catanzaro; Atrial Fibrillation Registry for Ankle-Brachial Index Prevalence Assessment-Collaborative Italian Study. PARTICIPANTS: 897 AF patients on treatment with vitamin K antagonists. MAIN OUTCOME MEASURES: The relationship between basal ABI and renal function progression, assessed by the estimated Glomerular Filtration Rate (eGFR) calculated with the CKD-EPI formula at baseline and after 2 years of follow-up. The rapid decline in eGFR, defined as a decline in eGFR >5 mL/min/1.73 m(2)/year, and incident eGFR<60 mL/min/1.73 m(2) were primary and secondary end points, respectively. RESULTS: Mean age was 71.8±9.0 years and 41.8% were women. Low ABI (ie, ≤0.90) was present in 194 (21.6%) patients. Baseline median eGFR was 72.7 mL/min/1.73 m(2), and 28.7% patients had an eGFR60 mL/min/1.73 m(2), 153 (23.9%) had a reduction of the eGFR <60 mL/min/1.73 m(2). ABI ≤0.90 was also an independent predictor for incident eGFR<60 mL/min/1.73 m(2) (HR 1.851, 95% CI 1.205 to 2.845, p=0.005). CONCLUSIONS: In patients with AF, an ABI ≤0.90 is independently associated with a rapid decline in renal function and incident eGFR<60 mL/min/1.73 m(2). ABI measurement may help identify patients with AF at risk of renal function deterioration