Obesity is a complex disease and its prevalence depends on multiple factors related to the local socioeconomic, cultural and urban context of individuals. Many obesity prevention strategies and ...policies, however, are horizontal measures that do not depend on context-specific evidence. In this paper we present an overview of BigO (http://bigoprogram.eu), a system designed to collect objective behavioral data from children and adolescent populations as well as their environment in order to support public health authorities in formulating effective, context-specific policies and interventions addressing childhood obesity. We present an overview of the data acquisition, indicator extraction, data exploration and analysis components of the BigO system, as well as an account of its preliminary pilot application in 33 schools and 2 clinics in four European countries, involving over 4,200 participants.
The aim of this study was to investigate heart rate (HR) variability in patients with weaning failure or success, using both linear and nonlinear techniques. Thirty-two surgical patients were ...enrolled in the study. Signals were analyzed for 10 minutes during two phases: 1. pressure support (PS) ventilation (15-20 cm H 2 O) and 2. weaning trials with PS: 5 cm H 2 O. Low and high frequency (LF, HF) components of HR signals, HR multiscale entropy (MSE) and al exponent derived from detrended fluctuation analysis (DFA) were computed in all patients and during the two phases of PS. Weaning failure patients exhibited significantly decreased LF, HF and al exponent, whereas MSE increased both between and within groups.
A new method is presented, that uses wavelets in order to suppress distal activity and produce an estimate of the membrane current. It can improve current clinical techniques of electrogram ...interpretation, minimizing physician time required to manually mark activation time estimates and localize infarcted tissue. Spatial and temporal information are combined. The input is an array of electrograms positioned on grid-points of a rectangular grid. No assumption is required about the propagation velocity or grid-size. The output is an array of estimates of the membrane current. Wavelet transform is performed for all signals. For each time step and each scale, the common spatial component is rejected. Signals are reconstructed from the wavelet coefficients. As a post-processing step, activation times are calculated from the current estimates using time-based criteria. Extracellular potentials are calculated from the current estimates and compared with the experimental ones.
The human IGHV4-34 gene encodes antibodies which are intrinsically autoreactive when the VH domain is unmutated. Therefore, B cells expressing IGHV4-34 B-cell receptor immunoglobulins (BcR IG) are ...normally under close scrutiny in order to avoid unwanted autoreactivity, especially against DNA. The IGHV4-34 gene is frequently utilized in chronic lymphocytic leukemia (CLL), where, typically, it shows a high load of somatic hypermutation (SHM). We have previously reported distinctive SHM patterns amongst IGHV4-34 CLL, especially for subsets with stereotyped BcR IG. However, although a large number of cases (~2000) was previously studied, since even the largest subsets account for only ~3% of CLL, meaningful conclusions could not be reached for smaller subsets. Here we revisit this issue in a series of 16,528 CLL cases and focus on IGHV4-34 expressing subsets: #4 (IGHV4-34/IGHD5-18/IGHJ6 | 156 cases, 0.9%); #11 (IGHV4-34/IGHD3-10/IGHJ4 | 16 cases, 0.1%); #16 (IGHV4-34/IGHD2-15/IGHJ6 | 41 cases, 0.25%); #29 (IGHV4-34/IGHD: unassignable/IGHJ3 | 39 cases, 0.24%); and #201 (IGHV4-34/IGHD: unassignable/IGHJ3 | 43 cases 0.26%). Focusing on codons 27-104 within the VH domain (from CDR1-IMGT to FR3-IMGT), we calculated the sequence distance between subsets and the corresponding IGHV4-34 germline sequence based on a pairwise qualitative and quantitative comparison of the respective amino acid composition. The minimum distance calculated, and hence the greatest identity, was observed between subsets #4 and #16, both concerning IgG-switched cases (IgG-CLL), which is notable given the overall rarity of IgG-CLL. In contrast, the maximum distance, implying the least identity, was between subsets #16 and #201, the latter concerning IgM/D-CLL. Extreme variations between subsets were noted in codons spanning the entire VH domain. This result is consistent with our finding of a subset-biased distribution of mutations over the VH domain. More specifically, while subsets #11, #16, #29 and #201 had a lower frequency of mutations within VH CDR1 compared to VH CDR2, the exact opposite was seen in subset #4, with 40% of mutations in VH CDR1 versus 27% in VH CDR2. In addition, subsets #4, #11, #16 and #29 had a similar distribution of mutations in VH FR2 and VH FR3, in contrast to subset #201 that showed a preference for VH FR3 over VH FR2. Consequently, we noted that certain positions were targeted in a subset-specific manner e.g. codon 28 in VH CDR1 was heavily targeted in subsets #4 (68.6%) and #16 (87.8%), with most cases carrying an acidic amino acid (AA) introduced by SHM, glycine to glutamic acid, G>E: 51.3% for subset #4 and 78% for subset #16. The high prevalence of acidic AA introduced by SHM in these subsets is notable considering the electropositive nature of their VH CDR3 (especially of subset #4), strongly recalling edited anti-DNA antibodies. Interestingly, the G>E change was identified at a much lower frequency in other IGHV4-34 subsets: 18.75% for subset #11; 2.6% for subset #29; 7% for subset #201, all of which carried electronegative VH CDR3. Further, we noted that certain positions were heavily targeted in all subsets e.g. 56-86% targeting for SHM at codon 92 in VH FR3 where serine is encoded by the agc triplet, the ”hottest of hotspots”. This result could be viewed as sequence- rather than subset-dependent and linked to the molecular features of this codon, which is supported by the low targeting of codon 93 (0-6%), also encoding serine by the tct triplet. Other positions were targeted in all subsets but at vastly different frequencies e.g. codon 64 was targeted in 37.8% in subset #4 rising to 100% in subset #29. Finally, positions heavily targeted by SHM in certain subsets were unmutated in other subsets e.g. codon 36 in VH CDR1 remained unmutated in subset #16, in contrast 76.9% of subset #29 were mutated at this position resulting in an AA change. In conclusion, we document different spectra of SHM and AA changes between stereotyped IGHV4-34 CLL subsets. The finding of subset-biased, recurrent AA changes at certain codons indicates that the respective progenitor cells may have responded in a specific manner to the selecting antigen(s), despite expressing the same IGHV gene, indicating a functional purpose for these modifications. This is exemplified by the molecular characteristics of the recurrent AA changes in subset #4, thereby offering interesting pathogenetic hints.
No relevant conflicts of interest to declare.
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