Interlaboratory variability of MIB1 staining in well-differentiated pancreatic neuroendocrine tumors

Neuroendocrine tumors (NET) are routinely graded and staged to judge prognosis. Proliferation index using MIB1 staining has been introduced to assess grading. There are vivid discussions on cutoff definitions, automated counting, and interobserver variability. However, no data exist regarding interlaboratory reproducibility for low proliferation indices which are of importance to discriminate between G1 and G2 NET. We performed MIB1 staining in three different university hospital-based pathology laboratories on a tissue micro array (TMA) of a well-characterized patient cohort, containing pancreatic NET of 61 patients. To calculate the proliferation index, number of positive tumor nuclei was divided by the total number of tumor nuclei. Labeling index was compared to mitotic counts in whole tissue sections and to clinical outcome. Linear regression analysis, intraclass comparison, and log-rank analysis were performed. Intraclass correlation showed moderate-to-fair agreement. Especially low proliferating tumors were affected by interlaboratory differences. Log-rank analysis was performed for each lab and resulted in three different cutoffs (5.0, 3.0, and 0.5 %). Every calculated cutoff stratified the patient cohort to a significant extent for the underlying stain (p < 0.001, <0.001, and <0.001) but showed no or lesser significance when applied to the other stains. Significant and relevant interlab differences for MIB1 exist. Since the MIB1 proliferation index influences grading, local cutoffs or external standardization should urgently be introduced to achieve reliability and reproducibility.

Compensability index for compensation radiotherapy after treatment interruptions

Background The goal of our work was to develop a simple method to evaluate a compensation treatment after unplanned treatment interruptions with respect to their tumour- and normal tissue effect. Methods We developed a software tool in java programming language based on existing recommendations to compensate for treatment interruptions. In order to express and visualize the deviations from the originally planned tumour and normal tissue effects we defined the compensability index. Results The compensability index represents an evaluation of the suitability of compensatory radiotherapy in a single number based on the number of days used for compensation and the preference of preserving the originally planned tumour effect or not exceeding the originally planned normal tissue effect. An automated tool provides a method for quick evaluation of compensation treatments. Conclusions The compensability index calculation may serve as a decision support system based on existing and established recommendations.

The influence of body mass index on injury pattern in polytrauma: thorax as the main source of complications

Background: Obesity is a growing problem in industrial nations. The aim of this study was to determine the relationship between the body mass index (BMI) and the pattern of injury after polytrauma. Methods: This retrospective study included 651 patients with an injury severity score (ISS) ≥16 and aged ≥16 years who were subdivided into three groups: BMI < 25 kg/m2, BMI 25–30 kg/m2, and BMI > 30 kg/m2. The Abbreviated Injury Scale (AIS) was used to quantify the injuries in the different anatomical regions. The Murray score was assessed at admission and at its maximum during hospitalization to evaluate pulmonary problems. Data are presented as means ± standard errors of the means. One way analysis of variance, χ2 test and Kruskal-Wallis test were used for the analyses and the significance level was set at p < 0.05. Results: The AIS of the thorax was 3.2 ± 0.1 in the BMI < 25 kg/m2 group, 3.3 ± 0.1 in the BMI 25–30 kg/m2 group, and 2.8 ± 0.2 in the BMI > 30 kg/m2 group; p < 0.05. The Murray score at admission increased significantly with increasing BMI (0.8 ± 0.8 for BMI < 25 kg/m2, 0.9 ± 0.9 for BMI 25–30 kg/m2, and 1.0 ± 0.8 for BMI > 30 kg/m2; p < 0.05) as was the maximum Murray score during hospitalization (1.2 ± 0.9 for BMI < 25 kg/m2, 1.6 ± 1.0 for BMI 25–30 kg/m2, and 1.5 ± 0.9 for BMI > 30 kg/m2; p < 0.001). The number of ventilator days was also elevated significantly with increasing BMI (5.9 ± 0.4 for BMI < 25 kg/m2, 7.7 ± 0.8 for BMI 25–30 kg/m2, and 7.9 ± 1.6 for BMI > 30 kg/m2; p < 0.05). Conclusion: Overweight and obesity lead to a higher incidence of thoracic trauma in a polytrauma situation and may additionally handicap ventilation in an obstructive manner.

Splitting of a prevalent Mycobacterium bovis spoligotype by variable-number tandem-repeat typing reveals high heterogeneity in an evolving clonal group

Mycobacterium bovis populations in countries with persistent bovine tuberculosis usually show a prevalent spoligotype with a wide geographical distribution. This study applied mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) typing to a random panel of 115 M. bovis isolates that are representative of the most frequent spoligotype in the Iberian Peninsula, SB0121. VNTR typing targeted nine loci: ETR-A (alias VNTR2165), ETR-B (VNTR2461), ETR-D (MIRU4, VNTR580), ETR-E (MIRU31, VNTR3192), MIRU26 (VNTR2996), QUB11a (VNTR2163a), QUB11b (VNTR2163b), QUB26 (VNTR4052), and QUB3232 (VNTR3232). We found a high degree of diversity among the studied isolates (discriminatory index [D] = 0.9856), which were split into 65 different MIRU-VNTR types. An alternative short-format MIRU-VNTR typing targeting only the four loci with the highest variability values was found to offer an equivalent discriminatory index. Minimum spanning trees using the MIRU-VNTR data showed the hypothetical evolution of an apparent clonal group. MIRU-VNTR analysis was also applied to the isolates of 176 animals from 15 farms infected by M. bovis SB0121; in 10 farms, the analysis revealed the coexistence of two to five different MIRU types differing in one to six loci, which highlights the frequency of undetected heterogeneity.

Development and Validation of a Symptom-Based Activity Index for Adults with Eosinophilic Esophagitis

BACKGROUND & Aims: Standardized instruments are needed to assess the activity of eosinophilic esophagitis (EoE), to provide endpoints for clinical trials and observational studies. We aimed to develop and validate a patient-reported outcome (PRO) instrument and score, based on items that could account for variations in patients' assessments of disease severity. We also evaluated relationships between patients' assessment of disease severity and EoE-associated endoscopic, histologic, and laboratory findings. METHODS We collected information from 186 patients with EoE in Switzerland and the US (69.4% male; median age, 43 years) via surveys (n = 135), focus groups (n = 27), and semi-structured interviews (n = 24). Items were generated for the instruments to assess biologic activity based on physician input. Linear regression was used to quantify the extent to which variations in patient-reported disease characteristics could account for variations in patients' assessment of EoE severity. The PRO instrument was prospectively used in 153 adult patients with EoE (72.5% male; median age, 38 years), and validated in an independent group of 120 patients with EoE (60.8% male; median age, 40.5 years). RESULTS Seven PRO factors that are used to assess characteristics of dysphagia, behavioral adaptations to living with dysphagia, and pain while swallowing accounted for 67% of the variation in patients' assessment of disease severity. Based on statistical consideration and patient input, a 7-day recall period was selected. Highly active EoE, based on endoscopic and histologic findings, was associated with an increase in patient-assessed disease severity. In the validation study, the mean difference between patient assessment of EoE severity and PRO score was 0.13 (on a scale from 0 to 10). CONCLUSIONS We developed and validated an EoE scoring system based on 7 PRO items that assesses symptoms over a 7-day recall period. Clinicaltrials.gov number: NCT00939263.

Estimating the Reproduction Number of Ebola Virus (EBOV) During the 2014 Outbreak in West Africa

The 2014 Ebola virus (EBOV) outbreak in West Africa is the largest outbreak of the genus Ebolavirus to date. To better understand the spread of infection in the affected countries, it is crucial to know the number of secondary cases generated by an infected index case in the absence and presence of control measures, i.e., the basic and effective reproduction number. In this study, I describe the EBOV epidemic using an SEIR (susceptible-exposed-infectious-recovered) model and fit the model to the most recent reported data of infected cases and deaths in Guinea, Sierra Leone and Liberia. The maximum likelihood estimates of the basic reproduction number are 1.51 (95% confidence interval [CI]: 1.50-1.52) for Guinea, 2.53 (95% CI: 2.41-2.67) for Sierra Leone and 1.59 (95% CI: 1.57-1.60) for Liberia. The model indicates that in Guinea and Sierra Leone the effective reproduction number might have dropped to around unity by the end of May and July 2014, respectively. In Liberia, however, the model estimates no decline in the effective reproduction number by end-August 2014. This suggests that control efforts in Liberia need to be improved substantially in order to stop the current outbreak.

Rapid drop in the reproduction number during the Ebola outbreak in the Democratic Republic of Congo.

The Democratic Republic of Congo (DRC) experienced a confined rural outbreak of Ebola virus disease (EVD) with 69 reported cases from July to October 2014. Understanding the transmission dynamics during the outbreak can provide important information for anticipating and controlling future EVD epidemics. I fitted an EVD transmission model to previously published data of this outbreak and estimated the basic reproduction number R 0 = 5.2 (95% CI [4.0-6.7]). The model suggests that the net reproduction number Rt fell below unity 28 days (95% CI [25-34] days) after the onset of symptoms in the index case. This study adds to previous epidemiological descriptions of the 2014 EVD outbreak in DRC, and is consistent with the notion that a rapid implementation of control interventions helped reduce further spread.

High-precision confocal reflection measurement for two dimensional refractive index mapping of optical fibers

We introduce a new fiber-optical approach for reflection based refractive index mapping. Our approach leads to improved stability and reliability over existing free-space confocal instruments and significantly cuts alignment efforts and reduces the number of components needed. Other than properly cleaved fiber end-faces, this setup requires no additional sample preparation. The instrument is calibrated by means of a set of samples with known refractive indices. The index steps of commercially available fibers are measured accurately down to < 10⁻³. The precision limit of the instrument is currently of the order of 10⁻⁴.

Nonperturbative results for two-index conformal windows

Via large and small N c relations we derive nonperturbative results about the conformal window of two-index theories. Using Schwinger-Dyson methods as well as four-loops results we estimate subleading corrections and show that naive large number of colors extrapolations are unreliable when N c is less than about six. Nevertheless useful nonper-turbative inequalities for the size of the conformal windows, for any number of colors, can be derived. By further observing that the adjoint conformal window is independent of the number of colors we argue, among other things, that: the large N c two-index conformal window is twice the conformal window of the adjoint representation (which can be determined at small N c) expressed in terms of Dirac fermions; lattice results for adjoint matter can be used to provide independent information on the conformal dynamics of two-index theories such as SU(N c) with two and four symmetric Dirac flavors.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.