Insights from Magnetic Evoked Field Analysis in Patients with Wilson's Disease.

Aims: To study the latency, amplitude, and source localization of magnetic evoked field (MEF) responses to visual, auditory, and somatosensory stimuli in Wilson's disease (WD) using magnetoencephalography (MEG) and compare it with "healthy" controls, and correlate the observations with disease severity and brain MRI. Methods: MEF of 28 patients with neurological WD (age: 22.82 ± 5.8 years; M:F = 12:16) and 21 matched controls (age: 25.0 ± 4.6 years; M:F = 10:11) were recorded using MEG. Source localization was performed using standard models on the components of M100, M20, and M100 for visual, somatosensory, and auditory evoked fields, respectively and its latency/amplitude was correlated with disease severity. Results: There were significant differences in source location between control and WD during visual evoked field (VEF) and auditory evoked field (AEF) studies. Latencies of M20 (right-p = 0.02; left-p = 0.04) and M32 (right-p = 0.01) components of SSEF were significantly prolonged. The amplitude of M20 was significantly reduced in patients bilaterally (P = 0.001). There was a trend for the prolonged latency of M100 of VEF in patients (P = 0.09). Five patients had reduced right M145 compared to 8 controls. The left somatosensory evoked fields (SSEF) latency correlated with disease severity (P = 0.04). There was no significant correlation between major components of other MEF with disease severity or MRI score. Conclusions: This study, first of its kind to use MEF analysis in a large cohort of patients with WD, detected subclinical but a variable degree of abnormalities, most consistently of SSEF. It provides valuable insights of functioning and localization of various pathways in a disease known to have protean clinical manifestations and widespread MRI changes.

Systematic reconstruction of an effector-gene network reveals determinants of Salmonella cellular and tissue tropism.

The minimal genetic requirements for microbes to survive within multiorganism communities, including host-pathogen interactions, remain poorly understood. Here, we combined targeted gene mutagenesis with phenotype-guided genetic reassembly to identify a cooperative network of SPI-2 T3SS effector genes that are sufficient for Salmonella Typhimurium (STm) to cause disease in a natural host organism. Five SPI-2 effector genes support pathogen survival within the host cell cytoplasm by coordinating bacterial replication with Salmonella-containing vacuole (SCV) division. Unexpectedly, this minimal genetic repertoire does not support STm systemic infection of mice. In vivo screening revealed a second effector-gene network, encoded by the spv operon, that expands the life cycle of STm from growth in cells to deep-tissue colonization in a murine model of typhoid fever. Comparison between Salmonella infection models suggests how cooperation between effector genes drives tissue tropism in a pathogen group.

A Novel Interference Suppression Method for Interrupted Sampling Repeater Jamming Based on Singular Spectrum Entropy Function.

As a new type of jamming, the interrupted sampling repeater jamming (ISRJ) derived from the digital radio frequency memory (DRFM) technology, can generate coherent multiple false targets after pulse compression. At present, the traditional interference suppression method and its improved methods have insufficient characteristics and poor detection performance under the condition of low signal-to-noise ratio (SNR). Aiming at addressing this defect, this paper proposes an interference suppression method for ISRJ based on singular spectrum entropy function (SSEF) from the aspects of singular value decomposition (SVD) and information entropy theories. In this method, firstly, considering the local fine characteristics and extraction efficiency, an adaptive multi-scale segmentation (AMS) method is proposed. The purpose of this processing is to extend the salient characteristics while to smooth the similar ones. In AMS, the segmentation criterion based on average energy of segments and the constraint of minimum segmentation is also proposed, then the improved delay embedded matrix is established from the improved trajectory matrix by AMS and delay embedded mapping. Secondly, the singular spectrum of the improved delay embedded matrix is extracted by SVD. Thirdly, because the recognition algorithms based on singular spectrum analysis (SSA), classical SSE and other characteristics fail at low SNR, this paper proposes a characteristic named as SSEF retrieved from the Shannon entropy model. The following proposed entropy-based threshold detection is carried out on the echo signal to realize the band-pass filtering and interference suppression. Finally, experiment results show that in comparison with other interference suppression approaches, SSEF can increase the probability of target detection and the peak-to-side-lobe ratio (PSR) after pulse compression, which validates its stability to noise and jamming especially in the condition of low SNRs.