An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation

BACKGROUND PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. METHODS Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. RESULTS In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age of 40. CONCLUSIONS The PREDICT v2 is an improved prognostication and treatment benefit model compared with v1. The online version should continue to aid clinical decision making in women with early breast cancer

Claudin 1 Mediates TNFα-Induced Gene Expression and Cell Migration in Human Lung Carcinoma Cells

Epithelial-mesenchymal transition (EMT) is an important mechanism in carcinogenesis. To determine the mechanisms that are involved in the regulation of EMT, it is crucial to develop new biomarkers and therapeutic targets towards cancers. In this study, when TGFβ1 and TNFα were used to induce EMT in human lung carcinoma A549 cells, we found an increase in an epithelial cell tight junction marker, Claudin 1. We further identified that it was the TNFα and not the TGFβ1 that induced the fibroblast-like morphology changes. TNFα also caused the increase in Claudin-1 gene expression and protein levels in Triton X-100 soluble cytoplasm fraction. Down-regulation of Claudin-1, using small interfering RNA (siRNA), inhibited 75% of TNFα-induced gene expression changes. Claudin-1 siRNA effectively blocked TNFα-induced molecular functional networks related to inflammation and cell movement. Claudin-1 siRNA was able to significantly reduce TNF-enhanced cell migration and fibroblast-like morphology. Furthermore, over expression of Claudin 1 with a Claudin 1-pcDNA3.1/V5-His vector enhanced cell migration. In conclusion, these observations indicate that Claudin 1 acts as a critical signal mediator in TNFα-induced gene expression and cell migration in human lung cancer cells. Further analyses of these cellular processes may be helpful in developing novel therapeutic strategies

Local and Landscape Factors Determining Occurrence of Phyllostomid Bats in Tropical Secondary Forests

Neotropical forests are being increasingly replaced by a mosaic of patches of different successional stages, agricultural fields and pasture lands. Consequently, the identification of factors shaping the performance of taxa in anthropogenic landscapes is gaining importance, especially for taxa playing critical roles in ecosystem functioning. As phyllostomid bats provide important ecological services through seed dispersal, pollination and control of animal populations, in this study we assessed the relationships between phyllostomid occurrence and the variation in local and landscape level habitat attributes caused by disturbance. We mist-netted phyllostomids in 12 sites representing 4 successional stages of a tropical dry forest (initial, early, intermediate and late). We also quantitatively characterized the habitat attributes at the local (vegetation structure complexity) and the landscape level (forest cover, area and diversity of patches). Two focal scales were considered for landscape characterization: 500 and 1000 m. During 142 sampling nights, we captured 606 individuals representing 15 species and 4 broad guilds. Variation in phyllostomid assemblages, ensembles and populations was associated with variation in local and landscape habitat attributes, and this association was scale-dependent. Specifically, we found a marked guild-specific response, where the abundance of nectarivores tended to be negatively associated with the mean area of dry forest patches, while the abundance of frugivores was positively associated with the percentage of riparian forest. These results are explained by the prevalence of chiropterophilic species in the dry forest and of chiropterochorous species in the riparian forest. Our results indicate that different vegetation classes, as well as a multi-spatial scale approach must be considered for evaluating bat response to variation in landscape attributes. Moreover, for the long-term conservation of phyllostomids in anthropogenic landscapes, we must realize that the management of the habitat at the landscape level is as important as the conservation of particular forest fragments

Bezlotoxumab for Prevention of Recurrent Clostridium difficile Infection

BACKGROUND Clostridium difficile is the most common cause of infectious diarrhea in hospitalized patients. Recurrences are common after antibiotic therapy. Actoxumab and bezlotoxumab are human monoclonal antibodies against C. difficile toxins A and B, respectively. METHODS We conducted two double-blind, randomized, placebo-controlled, phase 3 trials, MODIFY I and MODIFY II, involving 2655 adults receiving oral standard-of-care antibiotics for primary or recurrent C. difficile infection. Participants received an infusion of bezlotoxumab (10 mg per kilogram of body weight), actoxumab plus bezlotoxumab (10 mg per kilogram each), or placebo; actoxumab alone (10 mg per kilogram) was given in MODIFY I but discontinued after a planned interim analysis. The primary end point was recurrent infection (new episode after initial clinical cure) within 12 weeks after infusion in the modified intention-to-treat population. RESULTS In both trials, the rate of recurrent C. difficile infection was significantly lower with bezlotoxumab alone than with placebo (MODIFY I: 17% [67 of 386] vs. 28% [109 of 395]; adjusted difference, −10.1 percentage points; 95% confidence interval [CI], −15.9 to −4.3; P<0.001; MODIFY II: 16% [62 of 395] vs. 26% [97 of 378]; adjusted difference, −9.9 percentage points; 95% CI, −15.5 to −4.3; P<0.001) and was significantly lower with actoxumab plus bezlotoxumab than with placebo (MODIFY I: 16% [61 of 383] vs. 28% [109 of 395]; adjusted difference, −11.6 percentage points; 95% CI, −17.4 to −5.9; P<0.001; MODIFY II: 15% [58 of 390] vs. 26% [97 of 378]; adjusted difference, −10.7 percentage points; 95% CI, −16.4 to −5.1; P<0.001). In prespecified subgroup analyses (combined data set), rates of recurrent infection were lower in both groups that received bezlotoxumab than in the placebo group in subpopulations at high risk for recurrent infection or for an adverse outcome. The rates of initial clinical cure were 80% with bezlotoxumab alone, 73% with actoxumab plus bezlotoxumab, and 80% with placebo; the rates of sustained cure (initial clinical cure without recurrent infection in 12 weeks) were 64%, 58%, and 54%, respectively. The rates of adverse events were similar among these groups; the most common events were diarrhea and nausea. CONCLUSIONS Among participants receiving antibiotic treatment for primary or recurrent C. difficile infection, bezlotoxumab was associated with a substantially lower rate of recurrent infection than placebo and had a safety profile similar to that of placebo. The addition of actoxumab did not improve efficacy. (Funded by Merck; MODIFY I and MODIFY II ClinicalTrials.gov numbers, NCT01241552 and NCT01513239.

Modeling &amp; analysis of an LTE-advanced receiver using mode-controlled dataflow

Current multi-functional embedded systems such as smartphones and tablets support multiple 2G/3G/4G radio standards including Long Term Evolution (LTE) and LTE-Advanced. LTE-Advanced is the latest industry standard that improves upon LTE by introducing several feature-rich and complex improvements. Moreover, both LTE and LTE-Advanced have real-time requirements. LTE and LTE-Advanced receivers are typically scheduled on a heterogeneous multi-core processor to satisfy real-time and low-power requirements.\u3cbr/\u3e\u3cbr/\u3eManual simulation-based real-time analysis of such applications is infeasible. Dataflow can be used for real-time analysis. Static dataflow allows a rich set of analysis techniques to support real-time scheduling, but is too restrictive to accurately and conveniently model the dynamic data-dependent behavior for many practical applications, including LTE-Advanced. Dynamic dataflow allows modeling of such applications, but in general does not support rigorous real-time analysis.\u3cbr/\u3e\u3cbr/\u3eMode-controlled Dataflow (MCDF) is a restricted form of dynamic dataflow that captures realistic features in such applications and allows rigorous timing analysis. We stepwise refine and develop complete and fine-grained MCDF models of an LTE-Advanced receiver that include two key features: 1) carrier aggregation and 2) enhanced physical downlink control channel processing. We schedule the MCDF models on an industrial platform to benchmark them against (static) Single-rate Dataflow (SRDF) using existing buffer allocation techniques to demonstrate that these models are analyzable and practically applicable. Moreover, we also develop latency analysis techniques for single-rate and mode-controlled dataflow. For our LTE-Advanced receiver, relative to SRDF models, MCDF models offer 1) up to 15% smaller memory consumption, and 2) up to 1.6% smaller LTE-Advanced sub-frame processing latency