Security Risk Intelligent Assessment of Power Distribution Internet of Things via Entropy-Weight Method and Cloud Model.

The current power distribution Internet of Things (PDIoT) lacks security protection terminals and techniques. Network security has a large exposure surface that can be attacked from multiple paths. In addition, there are many network security vulnerabilities and weak security protection capabilities of power distribution Internet of Things terminals. Therefore, it is crucial to conduct a scientific assessment of the security of PDIoT. However, traditional security assessment methods are relatively subjective and ambiguous. To address the problems, we propose to use the entropy-weight method and cloud model theory to assess the security risk of the PDIoT. We first analyze the factors of security risks in PDIoT systems and establish a three-layer PDIoT security evaluation index system, including a perception layer, network layer, and application layer. The index system has three first-level indicators and sixteen second-level indicators. Then, the entropy-weight method is used to optimize the weight of each index. Additionally, the cloud model theory is employed to calculate the affiliation degree and eigenvalue of each evaluation index. Based on a comprehensive analysis of all evaluation indexes, we can achieve the security level of PDIoT. Taking the PDIoT of Meizhou Power Supply Bureau of Guangdong Power Grid as an example for empirical testing, the experimental results show that the evaluation results are consistent with the actual situation, which proves that the proposed method is effective and feasible.

Osteonecrosis in systemic lupus erythematosus: Systematic insight from the epidemiology, pathogenesis, diagnosis and management.

Osteonecrosis (ON) is one of the serious and well recognized complicationscausing severe pain and disability in patients with systemic lupus erythematosus (SLE), and its manifestation and pathogenesis are only partially understood. This review provide an update of the recent progress in etiology, pathogenesis, diagnosis, and treatment of systemic lupus erythematosus related osteonecrosis (SLE-ON). Despite the concomitant use of corticosteroids, alcohol and obesity, the dysregulated immune micro-environment and the complex pathogenesis of SLE synergistically play important roles in the development of ON. Osteonecrosis of femoral head (ONFH) is the most often involved joint in SLE. The current classification and staging system of ONFH is based on imaging techniques, particularly relating to MRI and CT, for the identification and quantification of necrotic lesions. For SLE-ONFH patients, both SLE specific clinical symptoms and ONFH imaging findings should be comprehensively evaluated. Even though advances concerning bone grafting and arthroplasty procedures have resulted in improved clinical outcomes, early pharmacological treatment at the pre-collapse stage may prevent joint collapse and reduce the joint arthroplasty rate, and this needs to be accounted. Although some progress has been made, considerably more research is needed before we fully understand SLE-ONFH. Future treatments of SLE-ONFH may involve genetic or cell-based therapies that target potential biomarkers, and this will lead to effective measures for saving thefunction of hip joint and preventing osteonecrosis.

Deep Learning-Based Artificial Intelligence System for Automatic Assessment of Glomerular Pathological Findings in Lupus Nephritis.

Accurate assessment of renal histopathology is crucial for the clinical management of patients with lupus nephritis (LN). However, the current classification system has poor interpathologist agreement. This paper proposes a deep convolutional neural network (CNN)-based system that detects and classifies glomerular pathological findings in LN. A dataset of 349 renal biopsy whole-slide images (WSIs) (163 patients with LN, periodic acid-Schiff stain, 3906 glomeruli) annotated by three expert nephropathologists was used. The CNN models YOLOv4 and VGG16 were employed to localise the glomeruli and classify glomerular lesions (slight/severe impairments or sclerotic lesions). An additional 321 unannotated WSIs from 161 patients were used for performance evaluation at the per-patient kidney level. The proposed model achieved an accuracy of 0.951 and Cohen's kappa of 0.932 (95% CI 0.915-0.949) for the entire test set for classifying the glomerular lesions. For multiclass detection at the glomerular level, the mean average precision of the CNN was 0.807, with 'slight' and 'severe' glomerular lesions being easily identified (F1: 0.924 and 0.952, respectively). At the per-patient kidney level, the model achieved a high agreement with nephropathologist (linear weighted kappa: 0.855, 95% CI: 0.795-0.916, p < 0.001; quadratic weighted kappa: 0.906, 95% CI: 0.873-0.938, p < 0.001). The results suggest that deep learning is a feasible assistive tool for the objective and automatic assessment of pathological LN lesions.

A Comprehensive Assessment of Hip Damage in Ankylosing Spondylitis, Especially Early Features.

Ankylosing spondylitis (AS) is most common in adolescents and the ultimate result is disability, which places a huge burden on patients and society. Therefore, the key to improve the prognosis of AS is the early diagnosis of hip injury. To examine if AS patients whose hip pain is either absent or minimal might already have observable MRI and X-ray hip changes. Clinical and imaging hip data were systematically analyzed in 200 healthy controls (HC) and 300 AS with varying degrees of hip pain. Forty-four patients with early hip osteoarthritis (OA) served as positive imaging controls. In MRI images, BME lesions in the STIR sequence were much more frequent in AS (62%) compared to HC (2%) (p < 0.0001). Most importantly, 42% of AS with no or minimal hip pain had one or more MRI lesions. This was much more frequent compared to the 2% in HC (p < 0.05). These lesions in AS were observed singly or in combination in the trochanters (8%), femoral heads (12%), and acetabula (13%). Parallel finding that X-ray changes were present in patients with minimal or no hip pain was also observed with X-ray. Based on the normal hip width of HC, joint space narrowing was observed in 94.3% of the entire AS cohort, and importantly 56.7% of AS patients with no or mild hip pain. In these latter patients, functional activities of the hips such as walking were normal. At least 40% of AS patients with minimal or no hip pain might already show MRI and X-ray changes.

Performance of the PET vascular activity score (PETVAS) for qualitative and quantitative assessment of inflammatory activity in Takayasu's arteritis patients.

PURPOSE: To assess the performance of PET vascular activity score (PETVAS) in comparison with SUVmax, inflammatory biomarkers and ITAS-2010 score in a cohort of TAK patients. METHODS: Sixty-four PET/CT scans acquired from 54 TAK patients were analyzed. The inflammatory activity was qualitatively determined by physician's global assessment and quantitatively determined by ITAS-2010 score. SUVmax and PETVAS were acquired by consensus review. Levels of the inflammatory biomarkers C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and pentraxin-3 (PTX-3) were measured. Performance of the qualitative diagnoses and the quantitative correlation were, respectively, compared by receiver operating characteristic (ROC) curve and Spearman correlation coefficient. RESULTS: The biomarkers (CRP, ESR, PTX-3), PET uptake values (SUVmax, PETVAS), and ITAS-2010 scores were all significantly higher in active patients than in non-active ones. The area under the ROC curve and Youden Index of PETVAS and PTX-3 were higher than those of SUVmax, CRP, ESR, and ITAS-2010. PETVAS and PTX-3 resulted in a higher Spearman correlation coefficient with ITAS-2010 than other criteria, either among all patients or within the active group. Alteration trends of PETVAS and PTX-3 during follow-up showed a tighter correlation with clinical progression/remission assessment than other criteria. CONCLUSIONS: In TAK evaluation, PETVAS is superior for qualitative and quantitative assessment, compared with the regional SUVmax. Compared to CRP and ESR, inflammatory biomarker PTX-3 shows better qualitative performance and a higher correlation with PETVAS and ITAS-2010. These findings indicate that the use of PETVAS and PTX-3, instead of SUVmax and CRP/ESR, has potential advantages in the clinical evaluation of TAK.