Stochastic rank correlation: a robust merit function for 2D/3D registration of image data obtained at different energies

In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

Long-term trends of HIV type 1 drug resistance prevalence among antiretroviral treatment-experienced patients in Switzerland

BACKGROUND:Accurate quantification of the prevalence of human immunodeficiency virus type 1 (HIV-1) drug resistance in patients who are receiving antiretroviral therapy (ART) is difficult, and results from previous studies vary. We attempted to assess the prevalence and dynamics of resistance in a highly representative patient cohort from Switzerland. METHODS:On the basis of genotypic resistance test results and clinical data, we grouped patients according to their risk of harboring resistant viruses. Estimates of resistance prevalence were calculated on the basis of either the proportion of individuals with a virologic failure or confirmed drug resistance (lower estimate) or the frequency-weighted average of risk group-specific probabilities for the presence of drug resistance mutations (upper estimate). RESULTS:Lower and upper estimates of drug resistance prevalence in 8064 ART-exposed patients were 50% and 57% in 1999 and 37% and 45% in 2007, respectively. This decrease was driven by 2 mechanisms: loss to follow-up or death of high-risk patients exposed to mono- or dual-nucleoside reverse-transcriptase inhibitor therapy (lower estimates range from 72% to 75%) and continued enrollment of low-risk patients who were taking combination ART containing boosted protease inhibitors or nonnucleoside reverse-transcriptase inhibitors as first-line therapy (lower estimates range from 7% to 12%). A subset of 4184 participants (52%) had >or= 1 study visit per year during 2002-2007. In this subset, lower and upper estimates increased from 45% to 49% and from 52% to 55%, respectively. Yearly increases in prevalence were becoming smaller in later years. CONCLUSIONS:Contrary to earlier predictions, in situations of free access to drugs, close monitoring, and rapid introduction of new potent therapies, the emergence of drug-resistant viruses can be minimized at the population level. Moreover, this study demonstrates the necessity of interpreting time trends in the context of evolving cohort populations.

An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods

In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

A communication and information technology infrastructure for real time monitoring and management of type 1 diabetes patients

This paper is focused on the integration of state-of-the-art technologies in the fields of telecommunications, simulation algorithms, and data mining in order to develop a Type 1 diabetes patient's semi to fully-automated monitoring and management system. The main components of the system are a glucose measurement device, an insulin delivery system (insulin injection or insulin pumps), a mobile phone for the GPRS network, and a PDA or laptop for the Internet. In the medical environment, appropriate infrastructure for storage, analysis and visualizing of patients' data has been implemented to facilitate treatment design by health care experts.

Neural network based glucose - insulin metabolism models for children with Type 1 diabetes

In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.

A real time simulation model of glucose-insulin metabolism for type 1 diabetes patients

In this paper, a simulation model of glucose-insulin metabolism for Type 1 diabetes patients is presented. The proposed system is based on the combination of Compartmental Models (CMs) and artificial Neural Networks (NNs). This model aims at the development of an accurate system, in order to assist Type 1 diabetes patients to handle their blood glucose profile and recognize dangerous metabolic states. Data from a Type 1 diabetes patient, stored in a database, have been used as input to the hybrid system. The data contain information about measured blood glucose levels, insulin intake, and description of food intake, along with the corresponding time. The data are passed to three separate CMs, which produce estimations about (i) the effect of Short Acting (SA) insulin intake on blood insulin concentration, (ii) the effect of Intermediate Acting (IA) insulin intake on blood insulin concentration, and (iii) the effect of carbohydrate intake on blood glucose absorption from the gut. The outputs of the three CMs are passed to a Recurrent NN (RNN) in order to predict subsequent blood glucose levels. The RNN is trained with the Real Time Recurrent Learning (RTRL) algorithm. The resulted blood glucose predictions are promising for the use of the proposed model for blood glucose level estimation for Type 1 diabetes patients.

Ragu: a free tool for the analysis of EEG and MEG event-related scalp field data using global randomization statistics

We present a program (Ragu; Randomization Graphical User interface) for statistical analyses of multichannel event-related EEG and MEG experiments. Based on measures of scalp field differences including all sensors, and using powerful, assumption-free randomization statistics, the program yields robust, physiologically meaningful conclusions based on the entire, untransformed, and unbiased set of measurements. Ragu accommodates up to two within-subject factors and one between-subject factor with multiple levels each. Significance is computed as function of time and can be controlled for type II errors with overall analyses. Results are displayed in an intuitive visual interface that allows further exploration of the findings. A sample analysis of an ERP experiment illustrates the different possibilities offered by Ragu. The aim of Ragu is to maximize statistical power while minimizing the need for a-priori choices of models and parameters (like inverse models or sensors of interest) that interact with and bias statistics.

Combining follow-up and change data is valid in meta-analyses of continuous outcomes: a meta-epidemiological study

OBJECTIVE To investigate whether it is valid to combine follow-up and change data when conducting meta-analyses of continuous outcomes. STUDY DESIGN AND SETTING Meta-epidemiological study of randomized controlled trials in patients with osteoarthritis of the knee/hip, which assessed patient-reported pain. We calculated standardized mean differences (SMDs) based on follow-up and change data, and pooled within-trial differences in SMDs. We also derived pooled SMDs indicating the largest treatment effect within a trial (optimistic selection of SMDs) and derived pooled SMDs from the estimate indicating the smallest treatment effect within a trial (pessimistic selection of SMDs). RESULTS A total of 21 meta-analyses with 189 trials with 292 randomized comparisons in 41,256 patients were included. On average, SMDs were 0.04 standard deviation units more beneficial when follow-up values were used (difference in SMDs: -0.04; 95% confidence interval: -0.13, 0.06; P=0.44). In 13 meta-analyses (62%), there was a relevant difference in clinical and/or significance level between optimistic and pessimistic pooled SMDs. CONCLUSION On average, there is no relevant difference between follow-up and change data SMDs, and combining these estimates in meta-analysis is generally valid. Decision on which type of data to use when both follow-up and change data are available should be prespecified in the meta-analysis protocol.

Comparing Haemophilus influenzae type b conjugate vaccine schedules: a systematic review and meta-analysis of vaccine trials

BACKGROUND The optimal schedule and the need for a booster dose are unclear for Haemophilus influenzae type b (Hib) conjugate vaccines. We systematically reviewed relative effects of Hib vaccine schedules. METHODS We searched 21 databases to May 2010 or June 2012 and selected randomized controlled trials or quasi-randomized controlled trials that compared different Hib schedules (3 primary doses with no booster dose [3p+0], 3p+1 and 2p+1) or different intervals in primary schedules and between primary and booster schedules. Outcomes were clinical efficacy, nasopharyngeal carriage and immunological response. Results were combined in random-effects meta-analysis. RESULTS Twenty trials from 15 countries were included; 16 used vaccines conjugated to tetanus toxoid (polyribosylribitol phosphate conjugated to tetanus toxoid). No trials assessed clinical or carriage outcomes. Twenty trials examined immunological outcomes and found few relevant differences. Comparing polyribosylribitol phosphate conjugated to tetanus toxoid 3p+0 with 2p+0, there was no difference in seropositivity at the 1.0 μg/mL threshold by 6 months after the last primary dose (combined risk difference -0.02; 95% confidence interval: -0.10, 0.06). Only small differences were seen between schedules starting at different ages, with different intervals between primary doses, or with different intervals between primary and booster doses. Individuals receiving a booster were more likely to be seropositive than those at the same age who did not. CONCLUSIONS There is no clear evidence from trials that any 2p+1, 3p+0 or 3p+1 schedule of Hib conjugate vaccine is likely to provide better protection against Hib disease than other schedules. Until more data become available, scheduling is likely to be determined by epidemiological and programmatic considerations in individual settings.

Experimental adaptation of wild-type canine distemper virus (CDV) to the human entry receptor CD150.

Canine distemper virus (CDV), a close relative of measles virus (MV), is widespread and well known for its broad host range. When the goal of measles eradication may be achieved, and when measles vaccination will be stopped, CDV might eventually cross the species barrier to humans and emerge as a new human pathogen. In order to get an impression how fast such alterations may occur, we characterized required adaptive mutations to the human entry receptors CD150 (SLAM) and nectin-4 as first step to infect human target cells. Recombinant wild-type CDV-A75/17(red) adapted quickly to growth in human H358 epithelial cells expressing human nectin-4. Sequencing of the viral attachment proteins (hemagglutinin, H, and fusion protein, F) genes revealed that no adaptive alteration was required to utilize human nectin-4. In contrast, the virus replicated only to low titres (10(2) pfu/ml) in Vero cells expressing human CD150 (Vero-hSLAM). After three passages using these cells virus was adapted to human CD150 and replicated to high titres (10(5) pfu/ml). Sequence analyses revealed that only one amino acid exchange in the H-protein at position 540 Asp→Gly (D540G) was required for functional adaptation to human CD150. Structural modelling suggests that the adaptive mutation D540G in H reflects the sequence alteration from canine to human CD150 at position 70 and 71 from Pro to Leu (P70L) and Gly to Glu (G71E), and compensates for the gain of a negative charge in the human CD150 molecule. Using this model system our data indicate that only a minimal alteration, in this case one adaptive mutation, is required for adaptation of CDV to the human entry receptors, and help to understand the molecular basis why this adaptive mutation occurs.

Testing an alternative search algorithm for compound identification with the 'Wiley Registry of Tandem Mass Spectral Data. MSforID'

A tandem mass spectral database system consists of a library of reference spectra and a search program. State-of-the-art search programs show a high tolerance for variability in compound-specific fragmentation patterns produced by collision-induced decomposition and enable sensitive and specific 'identity search'. In this communication, performance characteristics of two search algorithms combined with the 'Wiley Registry of Tandem Mass Spectral Data, MSforID' (Wiley Registry MSMS, John Wiley and Sons, Hoboken, NJ, USA) were evaluated. The search algorithms tested were the MSMS search algorithm implemented in the NIST MS Search program 2.0g (NIST, Gaithersburg, MD, USA) and the MSforID algorithm (John Wiley and Sons, Hoboken, NJ, USA). Sample spectra were acquired on different instruments and, thus, covered a broad range of possible experimental conditions or were generated in silico. For each algorithm, more than 30,000 matches were performed. Statistical evaluation of the library search results revealed that principally both search algorithms can be combined with the Wiley Registry MSMS to create a reliable identification tool. It appears, however, that a higher degree of spectral similarity is necessary to obtain a correct match with the NIST MS Search program. This characteristic of the NIST MS Search program has a positive effect on specificity as it helps to avoid false positive matches (type I errors), but reduces sensitivity. Thus, particularly with sample spectra acquired on instruments differing in their Setup from tandem-in-space type fragmentation, a comparably higher number of false negative matches (type II errors) were observed by searching the Wiley Registry MSMS.

Kyzylkumite, Ti2V3+O5(OH): new structure type, modularity and revised formula

The crystal structure of kyzylkumite, ideally Ti2V3+O5(OH), from the Sludyanka complex in South Baikal, Russia was solved and refined (including the hydrogen atom position) to an agreement index, R1, of 2.34 using X-ray diffraction data collected on a twinned crystal. Kyzylkumite crystallizes in space group P21/c, with a = 8.4787(1), b = 4.5624(1), c = 10.0330(1) Å, β = 93.174(1)°, V = 387.51(1) Å3 and Z = 4. Tivanite, TiV3+O3OH, and kyzylkumite have modular structures based on hexagonal close packing of oxygen, which are made up of rutile TiO2 and montroseite V3+O(OH) slices. In tivanite the rutile:montroseite ratio is 1:1, in kyzylkumite the ratio is 2:1. The montroseite module may be replaced by the isotypic paramontroseite V4+O2 module, which produces a phase with the formula Ti2V4+O6. In the metamorphic rocks of the Sludyanka complex, vanadium can be present as V4+ and V3+ within the same mineral (e.g. in batisivite, schreyerite and berdesinskiite). Kyzylkumite has a flexible composition with respect to the M4+/M3+ ratio. The relationship between kyzylkumite and a closely related Be-bearing kyzylkumite-like mineral with an orthorhombic norbergite-type structure from Byrud mine, Norway is discussed. Both minerals have similar X-ray powder diffraction patterns.

Metabolic control in children and adolescents with diabetes mellitus type I in Berne: a cross-sectional study.

AIMS/HYPOTHESIS In diabetes mellitus type I, good glycaemic control is crucial in preventing long-term diabetic complications. The aim of this study was to determine the current level of metabolic control in children and adolescents in our diabetes outpatient clinic at the University Children's Hospital, Berne. Furthermore, the impact of different factors such as age, pubertal stage, sex, duration of diabetes and insulin regimen on glycaemic control was studied. METHODS In a cross-sectional, prospective study 168 children and adolescents with type I diabetes mellitus (f:m = 87:81; prepubertal 48 [mean age 4.4 years, mean duration of diabetes 2.8 years]; pubertal 120 [mean age 9.4 years; mean duration of diabetes 5.2 years]) were studied for three months. Clinical data and HbA1c levels (latex immunoagglutination test) were recorded, statistically analysed and compared with the international literature. RESULTS In our type I diabetic children and adolescents the overall HbA1c was 8.07 +/- 1.15% (mean +/- SD; test-specific norm for healthy subjects: 4.1-6.1%). Glycaemic control was significantly worse in the pubertal group compared to the prepubertal (HbA1c 8.22 +/- 1.25% vs. 7.81 +/- 0.87%; p < 0.01). In addition, we found better metabolic control in patients with duration of diabetes below 2 years in children and adolescents (HbA1c prepubertal < 2 years: 7.45 +/- 0.67% vs. > 2 years: 8.05 +/- 0.93%, p < 0.05; pubertal < 2 years: 7.62 +/- 0.75% vs. > 2 years: 8.31 +/- 1.29%, p < 0.005). Importantly, sex and insulin regimen did not significantly influence glycaemic control. CONCLUSION/INTERPRETATION The current level of metabolic control in our children and adolescents with diabetes mellitus type I is comparable to the glycaemic control of the intensively treated adolescent group of the DCCT-study, in whom decreased risk of long-term diabetic complications was found. In contrast, our patients were intensively treated in terms of frequent contacts with the diabetes team, but were not necessarily on an intensified insulin regimen. The impact of biopsychosocial support from multidisciplinary diabetes team on good metabolic control in children and adolescents with type I diabetes mellitus and their families seems to be very important.

Co-activation of JAK/STAT and p38 MAPK pathways by type I interferon enhances apoptosis in human basophils

It has previously been published that interferon-α (type I IFN) improves clinical symptoms of asthma patients. Since human basophils are major inflammatory cells in maintaining chronic allergic asthma we investigate whether type I IFN affect human blood basophils. Furthermore, previous studies have shown that spontaneous apoptosis of human basophils is slow due to constitutive expression of anti-apoptotic BCL-2 family members. In addition, IL-3 exceptionally promotes survival of basophils by enhancing constitutive expression of BCL-2 family members and by inducing de-novo expression of Pim-1 kinase. Thus, we also assessed whether type I IFN might overcome IL-3-induced survival of human basophils. Our data show that type I IFN enhances apoptosis in purified human blood basophils compared to spontaneous apoptosis of controls or type II IFN treated cells. Furthermore, we demonstrate that both type I IFN and FasL enhance apoptosis in human basophils with similar efficiency in a rather additive than synergistic way. Analyses of signaling pathways reveal that type I IFN promote prolonged phosphorylation of STAT1/STAT2. By using a pan-JAK inhibitor the phosphorylation of STAT1/STAT2 is inhibited and most importantly the pro-apoptotic effect of type I IFN is abolished. On the other hand, type I IFN do not reduce IL-3-induced de novo expression of Pim-1 and BCL-2. This is in line with our observation that IL-3-induced survival is dominant over type I IFN-enhanced apoptosis. In addition, phosphorylation of p38 MAPK in type I IFN treated cells is comparable to non-treated cells. Particularly however, inhibition of this p-p38 activity abrogates apoptosis as well. We conclude that type I IFN-enhanced apoptosis is tightly regulated by the cooperation of JAK/STAT and p38 MAPK pathways. Our study identifies a so far unknown effect of type I IFN and may explain the improved clinical symptoms of asthma patients treated with type I IFN.

High-Pressure Behavior and Phase Stability of Al5BO9, a Mullite-Type Ceramic Material

Phase stability, elastic behavior, and pressure-induced structural evolution of synthetic boron-mullite Al5BO9 (a = 5.6780(7), b = 15.035(6), and c =7.698(3) Å, space group Cmc21, Z = 4) were investigated up to 25.6(1) GPa by in situ single-crystal synchrotron X-ray diffraction with a diamond anvil cell (DAC) under hydrostatic conditions. No evidence of phase transition was observed up to 21.7(1) GPa. At 25.6(1) GPa, the refined unit-cell parameters deviated significantly from the compressional trend, and the diffraction peaks appeared broader than at lower pressure. At 26.7(1) GPa, the diffraction pattern was not indexable, suggesting amorphization of the material or a phase transition to a high-pressure polymorph. Fitting the P–V data up to 21.7(1) GPa with a second-order Birch–Murnaghan Equation-of-State, we obtained a bulk modulus KT0 = 164(1) GPa. The axial compressibilities, here described as linearized bulk moduli, are as follows: KT0(a) = 244(9), KT0(b) = 120(4), and KT0(c) = 166(11) GPa (KT0(a):KT0(b):KT0(c) = 2.03:1:1.38). The structure refinements allowed a description of the main deformation mechanisms in response to the applied pressure. The stiffer crystallographic direction appears to be controlled by the infinite chains of edge-sharing octahedra running along [100], making the structure less compressible along the a-axis than along the b- and c-axis.