Data from magnetoencephalography (MEG) and electroencephalography (EEG) suffer from a rather limited signal-to-noise-ratio (SNR) due to cortical background activities and other artifacts. In order to study the effect of the SNR on the size and distribution of dipole clusters reconstructed from interictal epileptic spikes, we performed simulations using realistically shaped volume conductor models and extended cortical sources with different sensor configurations. Head models and cortical surfaces were derived from an averaged magnetic resonance image dataset (Montreal Neurological Institute). Extended sources were simulated by spherical patches with Gaussian current distributions on the folded cortical surface. Different patch sizes were used to investigate cancellation effects from opposing walls of sulcal foldings and to estimate corresponding changes in MEG and EEG sensitivity distributions. Finally, white noise was added to the simulated fields and equivalent current dipole reconstructions were performed to determine size and shape of the resulting dipole clusters. Neuronal currents are oriented perpendicular to the local cortical surface and show cancellation effects of source components on opposing sulcal walls. Since these mostly tangential aspects from large cortical patches cancel out, large extended sources exhibit more radial components in the head geometry. This effect has a larger impact on MEG data as compared to EEG, because in a spherical head model radial currents do not yield any magnetic field. Confidence volumes of single reconstructed dipoles from simulated data at different SNRs show a good correlation with the extension of clusters from repeated dipole reconstructions. Size and shape of dipole clusters reconstructed from extended cortical sources do not only depend on spike and timepoint selection, but also strongly on the SNR of the measured interictal MEG or EEG data. In a linear approximation the size of the clusters is proportional to the inverse SNR.
Artifacts ; Dataset ; Electroencephalography* ; Head ; Magnetic Fields ; Magnetoencephalography ; Neurons ; Noise

Establishing the significance of observed effects is a preliminary requirement for any meaningful interpretation of clinical and experimental Electroencephalography or Magnetoencephalography (MEG) data. We propose a method to evaluate significance on the level of sensors whilst retaining full temporal or spectral resolution. Input data are multiple realizations of sensor data. In this context, multiple realizations may be the individual epochs obtained in an evoked-response experiment, or group study data, possibly averaged within subject and event type, or spontaneous events such as spikes of different types. In this contribution, we apply Statistical non-Parametric Mapping (SnPM) to MEG sensor data. SnPM is a non-parametric permutation or randomization test that is assumption-free regarding distributional properties of the underlying data. The method, referred to as Maps SnPM, is demonstrated using MEG data from an auditory mismatch negativity paradigm with one frequent and two rare stimuli and validated by comparison with Topographic Analysis of Variance (TANOVA). The result is a time- or frequency-resolved breakdown of sensors that show consistent activity within and/or differ significantly between event or spike types. TANOVA and Maps SnPM were applied to the individual epochs obtained in an evoked-response experiment. The TANOVA analysis established data plausibility and identified latencies-of-interest for further analysis. Maps SnPM, in addition to the above, identified sensors of significantly different activity between stimulus types.
Electroencephalography ; Magnetoencephalography ; Methods ; Random Allocation

BACKGROUND: Fat grafting, or lipofilling, represent frequent clinically used entities. The fate of these transplants is still not predictable, whereas only few animal models are available for further research. Quantum dots (QDs) are semiconductor nanocrystals which can be conveniently tracked in vivo due to photoluminescence. METHODS: Fat grafts in cluster form were labeled with cadmium-telluride (CdTe)-QD 770 and transplanted subcutaneously in a murine in vivo model. Photoluminescence levels were serially followed in vivo. RESULTS: Tracing of fat grafts was possible for 50 days with CdTe-QD 770. The remaining photoluminescence was 4.9%±2.5% for the QDs marked fat grafts after 30 days and 4.2%± 1.7% after 50 days. There was no significant correlation in the relative course of the tracking signal, when vital fat transplants were compared to non-vital graft controls. CONCLUSIONS: For the first-time fat grafts were tracked in vivo with CdTe-QDs. CdTe-QDs could offer a new option for in vivo tracking of fat grafts for at least 50 days, but do not document vitality of the grafts.
Adipocytes ; Adipose Tissue* ; Models, Animal ; Quantum Dots* ; Transplantation ; Transplants*

Aberrant CXCR4/CXCL12 signaling is involved in many pathophysiological processes such as cancer and inflammatory diseases. A natural fragment of serum albumin, named EPI-X4, has previously been identified as endogenous peptide antagonist and inverse agonist of CXCR4 and is a promising compound for the development of improved analogues for the therapy of CXCR4-associated diseases. To generate optimized EPI-X4 derivatives we here performed molecular docking analysis to identify key interaction motifs of EPI-X4/CXCR4. Subsequent rational drug design allowed to increase the anti-CXCR4 activity of EPI-X4. The EPI-X4 derivative JM#21 bound CXCR4 and suppressed CXCR4-tropic HIV-1 infection more efficiently than the clinically approved small molecule CXCR4 antagonist AMD3100. EPI-X4 JM#21 did not exert toxic effects in zebrafish embryos and suppressed allergen-induced infiltration of eosinophils and other immune cells into the airways of animals in an asthma mouse model. Moreover, topical administration of the optimized EPI-X4 derivative efficiently prevented inflammation of the skin in a mouse model of atopic dermatitis. Thus, rationally designed EPI-X4 JM#21 is a novel potent antagonist of CXCR4 and the first CXCR4 inhibitor with therapeutic efficacy in atopic dermatitis. Further clinical development of this new class of CXCR4 antagonists for the therapy of atopic dermatitis, asthma and other CXCR4-associated diseases is highly warranted.