Familiarity expands space and contracts time

When humans draw maps, or make judgments about travel‐time, their responses are rarely accurate and are often systematically distorted. Distortion effects on estimating time to arrival and the scale of sketch‐maps reveal the nature of mental representation of time and space. Inspired by data from rodent entorhinal grid cells, we predicted that familiarity to an environment would distort representations of the space by expanding the size of it. We also hypothesized that travel‐time estimation would be distorted in the same direction as space‐size, if time and space rely on the same cognitive map. We asked international students, who had lived at a college in London for 9 months, to sketch a south‐up map of their college district, estimate travel‐time to destinations within the area, and mark their everyday walking routes. We found that while estimates for sketched space were expanded with familiarity, estimates of the time to travel through the space were contracted with familiarity. Thus, we found dissociable responses to familiarity in representations of time and space. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc.     

Screening of different interactions in oxo-manganese porphyrin dimers containing axial N-donor ligands: a theoretical study

A theoretical analysis for describing the dimeric assemblies of high-valent manganese(v)-oxo meso-tetraphenylporphyrin (TPP) ([(TPP)Mn^VO]₂²⁺) and meso-tetrakis(pentafluorophenyl)porphyrin (TPFPP) ([(TPFPP)Mn^VO]₂²⁺) in the presence of axial N-donor ligands is presented. Our theoretical results revealed two types interactions in dimers: a sandwich-like interaction between phenyl rings of porphyrin molecules, and a non-bonded T-shape interaction between nitrogen donors attached to Mn centers. The curvature in the geometry of porphyrin in the [(TPP)Mn^VO]₂²⁺/N-donor system is significantly smaller than that of [(TPFPP)Mn^VO]₂²⁺/N-donor system. Moreover, the Mn–N_(ax) distances in [(TPFPP)Mn^VO]₂²⁺/N-donor system are shorter than those of [(TPP)Mn^VO]₂²⁺/N-donor system. Also, the donor–acceptor interaction between the imidazoles and the Mn centers are stronger than those of the other ligands in both porphyrins. These results are supported by atoms in molecules (AIM) and natural bond orbital (NBO) analysis.

A DFT analysis for describing the dimeric assemblies of high-valent manganese(v)-oxo meso-tetraphenylporphyrin ([(TPP)Mn^VO]₂²⁺) and meso-tetrakis(pentafluorophenyl)porphyrin ([(TPFPP)Mn^VO]₂²⁺) in the presence of axial N-donor ligands is presented.     

Childhood central nervous system tumors at MAHAK’s Pediatric Cancer Treatment and Research Center (MPCTRC), Tehran,Iran

Purpose

As central nervous system (CNS) tumors account for second most common childhood malignancies and the first cause of mortality in children with cancer, improving treatment modalities can lead to increase the health care of patients. In this study, we examined the prevalence of childhood brain tumors in patients who referred to MAHAK’s Pediatric Cancer Treatment and Research Center (MPCTRC) for treatment.

Methods

A retrospective review of all children less than 15 years old with a CNS histologically proven tumor, who presented to MPCTRC from April 2007 to April 2010, was performed. Data was analyzed by SPSS version 19 with Kolmogorov–Smirnov and Chi-square tests.

Results

There were 198 (124 boys) children eligible for the study. The majority of the tumors were infratentorial (n?=?134), and the rest were supratentorial (n?=?60) and spinal (n?=?4) cases. The median age was 6.11?±?3.65 years old. Medulloblastoma (n?=?66), low-grade glioma (n?=?52), and high-grade glioma (n?=?40) were the most common tumors. The mean duration of follow-up was 21 months. At the time of this analysis, there were 105 (53 %) children alive, 82 (41.4 %) deaths, and 11 (5.6 %) lost for follow-up. The survival rate was 51.68?±?5.22 %.

Conclusions

In contrast of high rate of death in this study, other general characteristics can serve as benchmark for improving our care for children with brain tumors in Iran.     

Caesarean Delivery in South-Western Iran: Trends and Determinants in a Community-Based Survey

Objective

To assess trends in caesarean delivery and its associated factors in south-western Iran.

Subjects and Methods

This cross-sectional study was conducted from January 2007 to January 2010 in Fars province, Iran. All deliveries recorded in public and private hospitals were included. The Mann-Whitney U test, χ² test and multivariate logistic regression models were used for analysis of data. A p value less than 0.05 was considered significant.

Results

The rate of caesarean section for the whole sample of 139,159 increased from 51.6% in 2007 to 53.3% in 2009, which was statistically and clinically significant. The rate of caesarean delivery was significantly higher in primiparous compared to multiparous mothers. The rate increased steadily with the mother''s age. The most prevalent recorded reason for caesarean delivery was maternal request. Logistic regression analysis showed that maternal age, previous abortions, underlying maternal disease, gestational age and number of living children were key contributing factors to the choice of mode of delivery.

Conclusion

This study showed an increasing rate of caesarean delivery which should draw the attention of policymakers to factors associated with this mode of delivery.Key Words: Caesarean delivery, Iran, Trend     

Repeated PR1 and WT1 peptide vaccination in Montanide-adjuvant fails to induce sustained high-avidity, epitope-specific CD8+ T cells in myeloid malignancies

Background

We previously showed that vaccination with one dose of PR1 and WT1 peptides induces transient anti-leukemia immunity. We hypothesized that maintenance of a sustained anti-leukemia response may require frequent boost injections.

Design and Methods

Eight patients with myeloid malignancies were enrolled in this phase II study, and 6 completed 6 injections of PR1 and WT1 peptides in Montanide-adjuvant with GM-CSF, every two weeks.

Results

Both high- and low-avidity PR1 or WT1-specific CD8⁺ T cells were detected in all evaluable patients after the first vaccine dose. Repeated vaccination led to selective deletion of high avidity PR1- and WT1-specific CD8⁺ T cells and was not associated with significant reduction in WT1-expression. Additional boosting failed to increase vaccine-induced CD8⁺ T-cell frequencies further and in all patients the response was lost before the 6^th dose. PR1- or WT1-specific CD8⁺ T cells were not detected in bone marrow samples, excluding their preferential localization to this site. Following a booster injection three months after the 6^th vaccine dose, no high-avidity PR1 or WT1-specific CD8⁺ T cells could be detected, whereas low-avidity T cells were readily expanded.

Conclusions

These data support the immunogenicity of PR1 and WT1 peptide vaccines. However, repeated delivery of peptides with Montanide-adjuvant and GM-CSF leads to rapid loss of high-avidity peptide-specific CD8⁺ T cells. These results may offer an explanation for the lack of correlation between immune and clinical responses observed in a number of clinical trials of peptide vaccination. New approaches are needed to induce long-term high-avidity memory responses against leukemia antigens. (ClinicalTrials.gov Identifier: NCT00499772)     

Role of iron in cancer development by viruses

Increased levels of iron in body are attributed to higher cancer risk. Given the fact that 16% of all human cancers are caused by viral infections, iron is suggested to play an important role in carcinogenesis particularly those induced by viral infections. The present study provides an updated summary of the literature and the plausible mechanisms of iron involvement in cancer development by viruses. Our understanding about the interplay between viral infections and iron in different settings particularly cancer development is yet to be improved as it may shed a new light in development of new therapeutic strategies.     

Systemic lupus erythematosus in Iran: a study of 2280 patients over 33 years

Objective: Systemic lupus erythematosus (SLE) as a chronic autoimmune disease has a worldwide distribution. There is a wide variation in the natural history of SLE among different ethnic and geographic groups. The aim of this study was to show the manifestations of SLE in Iranian patients. Methods: The study was on manifestations of SLE according to the database of the Rheumatology Research Center (RRC), Tehran, Iran, on registered patients during the period of 1976 to 2009. Results: A total of 2280 SLE patients (2052 female and 228 male) were studied. The female : male ratio was 9 : 1 and the mean age at presentation was 24.4 ± 10.4 years. Prevalence of manifestations included: musculoskeletal (83.2%), cutaneous (81.1%), renal (65.4%), neuropsychiatric (23.4%), pulmonary (21.5%), cardiac (17.2%), and hematologic (66.4%) symptoms. There was positive antinuclear antibodies in 86.4% and anti‐DNA in 82.3% of patients. Overlap syndrome and positive family history with other autoimmune diseases were detected in 7.6% and 3.4% of patients, respectively. Conclusion: In our patients the prevalence of cutaneous involvement was similar to those of nearby countries (with similar climate). Renal involvement was seen more than some other countries especially more than European countries, while other manifestations (such as hematologic and joint involvement) were similar to European countries (with similar ethnicity). We may conclude that genetic and/or climatic factors may lead to different presentations of lupus.     

Determinants of Outbreak Detection Performance

Objective

To predict the performance of outbreak detection algorithms under different circumstances which will guide the method selection and algorithm configuration in surveillance systems, to characterize the dependence of the performance of detection algorithms on the type and severity of outbreak, to develop quantitative evidence about determinants of detection performance.

Introduction

The choice of outbreak detection algorithm and its configuration can result in important variations in the performance of public health surveillance systems. Our work aims to characterize the performance of detectors based on outbreak types. We are using Bayesian networks (BN) to model the relationships between determinants of outbreak detection and the detection performance based on a significant study on simulated data.

Methods

The simulated surveillance data that we used was generated by Surveillance Lab of McGill University using Simulation Analysis Platform [1] considering surveillance in an urban area to detect waterborne outbreaks due to the failure of a water treatment plant. We focus on predicting the performance of the C-family of algorithms, because they are widely used, state-of-art outbreak detection algorithms [2]. We investigate the influence of algorithm characteristics and outbreak characteristics in determining outbreak detection performance. The C1, C2, and C3 are distinguished by the configuration of 2 parameters,the guardband and memory. Generally, gradually increasing outbreaks can bias the test statistic upward, so the detection algorithm will fail to flag the outbreak. To avoid this situation, the C2 and C3 use a 2-day gap, guardband, between the baseline interval and the test interval. The C3 includes 2 recent observations, called memory, in the computation of the test statistic. The W2 algorithm is a modified version of the C2 which takes weekly patterns of surveillance time series into account [3]. In the W2, the baseline data is stratified to 2 distinct baselines: one for weekdays, the other for weekends. The W3 includes 2 recent observations of each baseline while calculating the test statistic in the corresponding baseline.We ran the C1, C2, C3, W2, and W3 on 18k simulated time series and measured the sensitivity and specificity of detection. Then we created the training data set of 5400000 instances. Each instance was the result of performance evaluation of an outbreak detection algorithm with a specific setting of parameters. In order to investigate the determinants of detection performance and reveal their effects quantitatively, we used BN to predict the performance based on algorithm characteristics and outbreak characteristics.

Results

We developed 2 BN models in the Weka machine learning software [4] using 5-fold cross-validation. The first BN determines the effect of the guardband, memory, alerting threshold, and the weekly pattern indicator (0 for C-algorithms, 1 for W-algorithms) and outbreak characteristics (contamination level and duration) on the sensitivity of detection. The value of sensitivity was mapped to 4 classes: (0, 0.3], (0.3, 0.6], (0.6, 0.9], (0.9, 1]. The developed BN correctly classified 67.74% of instances. The misclassification error was 0.9407. The second BN for predicting the specificity of detection correctly classified 95.895% of instances in 10 classes and the misclassification error was 0.2975.

Conclusions

The contamination level and duration of outbreaks, alerting threshold, memory, guardband, and whether the weekly pattern was considered or not influence the sensitivity and specificity of outbreak detection and given the C-algorithm parameter settings, we can predict outbreak detection performance quantitatively. In future work, we plan to investigate other predictors of performance and study how these predictions can be used in algorithm and policy choices.