Automatic Focal Cortical Dysplasiav(FCD) detection by Magnetic Resonance Image (MRI)

Nowadays, approximately 50 million people are suffering from epilepsy all over the world, of whom 30% have Focal Cortical Dysplasia (FCD), a malformation that occurs during brain cortical development. In clinical treatments, FCD lesions often have to be removed by resective surgery. Magnetic Resonance Imaging (MRI) is the most important clinical tool for identifying FCD lesions, and has allowed the diagnostic detection of FCD lesions in an increasing number of patients, leading to increased rates of successful resective surgery. However, detection of FCD lesions is still a challenging task because of various factors such as extremely subtle FCD malformations, complex convolutions of human cerebral cortex and partial volume effect due to imaging. Previous works develop MRI features of FCD lesions to highlight FCD regions. However, these MRI features also exist in Healthy Controls. We developed a new MRI features of FCD lesions, and use a multi-feature based method to perform automatic FCD detection. As a results, we improve the similarity index than the previous method. Sensitivity and specificity are also improved by proposed work. The proposed work can be a useful clinical tool to assist FCD detection

Association of urine autoantibodies with disease activity in systemic lupus erythematosus

ObjectiveThe presence of urinary autoantibodies in patients with systemic lupus erythematosus (SLE) has been confirmed by several studies; however, the significance of their presence in urine remains unclear. This study aims to further investigate the association between urine autoantibodies and disease activity as well as organ involvement in SLE.MethodsThis cross-sectional study included 89 SLE patients. Data collected included anti-nuclear antibody (ANA), anti-ENA antibodies, and anti-dsDNA antibody levels in both serum and urine, complement (C) 3, C4 levels in serum, SLE disease activity index-2000 (SLEDAI-2000), renal domains of SLEDAI (RSLEDAI) and non-renal SLEDAI (NRSLEDAI).ResultsThe rate of positive urine ANA (uANA) was 33.3% (29/87) among the enrolled patients. Compared to the uANA negative group, the positive group exhibited significantly higher SLEDAI-2000 scores (7.85 ± 5.88 vs. 18.69 ± 6.93, p < 0.001), RSLEDAI scores [0 (0, 4.0) vs. 12.0 (8.0, 16.0), p < 0.001], and NRSLEDAI [4 (2.0, 8.0) vs. 6.0 (4.0, 9.5), p = 0.038]. Patients with positive urine anti-Sm antibody demonstrated significantly elevated SLEDAI-2000 scores compared to those who were negative (25.0 ± 8.80 vs. 10.09 ± 6.63, p < 0.001). Similarly, they also had higher RSLEDAI [16.0 (12.0, 16.0) vs. 4.0 (0, 8.0), p < 0.001] and NRSLEDAI [9.5 (6.0, 13.5) vs. 4.0 (3.0, 8.0), p = 0.012], as well as a greater prevalence of renal involvement compared to their negative counterparts (100% vs. 58.2, p = 0.022). There was a positive correlation between uANA titer and both SLEDAI-2000 (rs = 0.663, p < 0.001) and RSLEDAI (rs = 0.662, p < 0.001). The serum anti-dsDNA antibody level did not exhibit a significant correlation with RSLEDAI (rs = 0.143, p = 0.182). Conversely, the urine anti-dsDNA antibody level demonstrated a significant positive correlation with RSLEDAI (rs = 0.529, p < 0.001).ConclusionUrine ANA is associated with both global SLEDAI and RSLEDAI scores. Urine anti-Sm antibody is associated with an increased incidence of renal involvement in SLE. The urine anti-dsDNA antibody level, rather than the serum anti-dsDNA antibody level, exhibits a significant association with RSLEDAI in SLE

Computer aided FCD lesion detection based on T1 MRI data

Focal cortical dysplasia (FCD) is a frequent cause of epilepsy and can be detected using brain magnetic resonance imaging (MRI). The FCD lesions in MRI images are characterized by blurring of the gray matter/white matter (GM/WM) junction, cortical thickening and hyper-intensity signal within lesional region compared with other cortical regions. However, detecting FCD lesions by means of visual inspection can be a very difficult task for radiologists because the lesions are very subtle. To assist physicians in detecting the FCD lesions more efficiently and reduce the false positive regions resulted from the existing methods, we propose an algorithm for automated FCD detection based on T1 MRI data

Optimal Resource Allocation for U-Shaped Parallel Split Learning

Split learning (SL) has emerged as a promising approach for model training without revealing the raw data samples from the data owners. However, traditional SL inevitably leaks label privacy as the tail model (with the last layers) should be placed on the server. To overcome this limitation, one promising solution is to utilize U-shaped architecture to leave both early layers and last layers on the user side. In this paper, we develop a novel parallel U-shaped split learning and devise the optimal resource optimization scheme to improve the performance of edge networks. In the proposed framework, multiple users communicate with an edge server for SL. We analyze the end-to-end delay of each client during the training process and design an efficient resource allocation algorithm, called LSCRA, which finds the optimal computing resource allocation and split layers. Our experimental results show the effectiveness of LSCRA and that U-shaped PSL can achieve a similar performance with other SL baselines while preserving label privacy. Index Terms: U-shaped network, split learning, label privacy, resource allocation, 5G/6G edge networks.Comment: 6 pages, 6 figure

Multiple classifier fusion and optimization for automatic focal cortical dysplasia detection on magnetic resonance images

In magnetic resonance (MR) images, detection of focal cortical dysplasia (FCD) lesion as a main pathological cue of epilepsy is challenging because of the variability in the presentation of FCD lesions. Existing algorithms appear to have sufficient sensitivity in detecting lesions but also generate large numbers of false-positive (FP) results. In this paper, we propose a multiple classifier fusion and optimization schemes to automatically detect FCD lesions in MR images with reduced FPs through constructing an objective function based on the F-score. Thus, the proposed scheme obtains an improved tradeoff between minimizing FPs and maximizing true positives. The optimization is achieved by incorporating the genetic algorithm into the work scheme. Hence, the contribution of weighting coefficients to different classifications can be effectively determined. The resultant optimized weightings are applied to fuse the classification results. A set of six typical FCD features and six corresponding Z-score maps are evaluated through the mean F-score from multiple classifiers for each feature. From the experimental results, the proposed scheme can automatically detect FCD lesions in 9 out of 10 patients while correctly classifying 31 healthy controls. The proposed scheme acquires a lower FP rate and a higher F-score in comparison with two state-of-the-art methods

Diverse and strain-specific metabolites patterns induced by fungal endophytes in grape cells of different varieties

The potential for endophytes to initiate changes in host secondary metabolism has been well documented. However, the mechanisms underlying endophyte-plant metabolic interactions are still poorly understood. Here, we analysed the effects of fungal endophytes on the metabolite profiles of grape cells from two cultivars: 'Cabernet Sauvignon' (CS) and 'Rose honey' (RH). Our results clearly showed that co-culture with endophytic fungi greatly modified the metabolic profiles in grape cells of both varieties. Treatments with endophytic fungal strains caused the numbers of detected metabolites to vary from 10 to 19 in CS cells and from 8 to 14 in RH cells. In addition, 5 metabolites were detected in all CS cell samples, while 4 metabolites were detected in all RH cell samples. Some endophytic fungal strains could even introduce novel metabolites into the co-cultured grape cells. The metabolic profiles of grape leaves shaped by endophytic fungi exhibited host selectivity and fungal strain specificity. In this assay, the fungal strains RH32 (Alternaria sp.) and MDR36 (Colletotrichum sp.) triggered an increased response of the detected metabolites, including the greatest increase in the metabolite contents in grape cells of both cultivars. No obvious effects in terms of metabolite numbers and contents in grape cells when co-cultured with fungal strains RH7 (Epicoccum sp.) and RH48 (Colletotrichum sp.) were observed. The results of this experiment suggest that endophytic fungi could be used to control the metabolic profiles of grapes and thus increase grape quality

Pathogenic Pseudorabies Virus, China, 2012

In 2012, an unprecedented large-scale outbreak of disease in pigs in China caused great economic losses to the swine industry. Isolates from pseudorabies virus epidemics in swine herds were characterized. Evidence confirmed that the pathogenic pseudorabies virus was the etiologic agent of this epidemic

Multicenter validation of the value of BASFI and BASDAI in Chinese ankylosing spondylitis and undifferentiated spondyloarthropathy patients

The objectives of this study were to evaluate the reliability of Bath ankylosing spondylitis functional index (BASFI) and Bath ankylosing spondylitis disease activity index (BASDAI) in Chinese ankylosing spondylitis (AS) and undifferentiated spondyloarthropathy (USpA) patients. 664 AS patients by the revised New York criteria for AS and 252 USpA patients by the European Spondyloarthropathy Study Group criteria were enrolled. BASDAI and BASFI questionnaires were translated into Chinese. Participants were required to fill in BASFI and BASDAI questionnaires again after 24 h. Moreover, BASDAI and BASFI were compared in AS patients receiving Enbrel or infliximab before and after treatment. For AS group, BASDAI ICC: 0.9502 (95% CI: 0.9330–0.9502, α = 0.9702), BASFI ICC: 0.9587 (95% CI: 0.9521–0.9645, α = 0.9789). For USpA group, BASDAI ICC: 0.9530 (95% CI: 0.9402–0.9632, α = 0.9760), BASFI ICC: 0.9900 (95% CI: 0.9871–0.9922, α = 0.9950). In the AS group, disease duration, occipital wall distance, modified Schober test, chest expansion, ESR, and CRP showed significant correlation with BASDAI and BASFI (all P < 0.01). In the USpA group, onset age, ESR, and CRP were significantly correlated with BASDAI (all P < 0.05), while modified Schober test, ESR, and CRP were significantly associated with BASFI (all P < 0.05). The change in BASDAI and BASFI via Enbrel or infliximab treatment showed a significant positive correlation (P < 0.01). The two instruments have good reliability and reference value regarding the evaluation of patient’s condition and anti-TNF-α treatment response