Security load frequency control model of interconnected power system based on deception attack.

The interconnected power system connects the power grids of different regions through transmission lines, achieving power interconnection and resource sharing. However, data is transmitted through open power networks and is more susceptible to network attacks. To improve the stability of interconnected power systems under deception attacks, three scenarios of system security load frequency control were studied. Based on the construction of a dynamic model of load frequency control, an event-triggered strategy was used to reduce the communication frequency between nodes, resulting in a reduction in the amount of network transmission data. A sliding mode controller was constructed to solve the problem of event-triggered sliding mode security load frequency control. Elastic event-triggered sliding mode load frequency control for interconnected power systems under mixed attacks. The simulation results showed that using the load frequency control model triggered by events, the load frequency deviation of the interconnected power system can be stabilized at around 12 seconds, effectively saving the cost of network resources. Under the regulation of the load frequency control model based on sliding mode control, the interconnected power system stabilized in 10 seconds, reducing the load of network transmission. The elastic event-triggered sliding mode load frequency control model can ensure stable transmission of power data under various attacks and has good anti-interference performance. The results of this study have played an important role in achieving the stability of power resource supply. Compared with previous studies on individual power systems, this study solves the attack problem of interconnected power systems and considers the frequency control problem of system security loads under mixed attacks, enabling the system to recover stability faster.

Interplay of endothelial-mesenchymal transition, inflammation, and autophagy in proliferative diabetic retinopathy pathogenesis.

Background: Assessment and validation of endothelial-mesenchymal transition (EndoMT) in the retinal endothelium of patients with proliferative diabetic retinopathy (PDR) at the level of retinal and vitreous specimens, and preliminary discussion of its regulatory mechanisms. Methods: Transcriptome sequencing profiles of CD31+ cells from 9 retinal fibrovascular mem-branes (FVMs) and 4 postmortem retinas were downloaded from GEO databases to analyze EndoMT-related differentially expressed genes (DEGs). Then, 42 PDR patients and 34 idiopathic macular holes (IMH) patients were enrolled as the PDR and control groups, respectively. Vitreous humor (VH) samples were collected, and the expression of EndoMT-related proteins was quantified by enzyme-linked immunosorbent assay. Results: A total of 5845 DEGs were identified, and we subsequently focused on the analysis of 24 EndoMT-related marker genes, including the trigger of EndoMT, endothelial genes, mesenchymal genes, transcription factors, inflammatory factors, and autophagy markers. Six of these genes were selected for protein assay validation in VH, showing increased mesenchymal marker (type I collagen α 2 chain, COL1A2) and decreased endothelial marker (VE-cadherin, CDH5) accompanied by increased TGFß, IL-1ß, LC3B and P62 in PDR patients. In addition, anti-VEGF therapy could enhance EndoMT-related phenotypes. Conclusions: EndoMT may underlie the pathogenesis of PDR, and the induction and regulation correlate with autophagy defects and the inflammatory response.

The landscape of immune checkpoint-related long non-coding RNAs core regulatory circuitry reveals implications for immunoregulation and immunotherapy responses.

Long non-coding RNAs (lncRNAs) could modulate expression of immune checkpoints (ICPs) by cooperating with immunity genes in tumor immunization. However, precise functions in immunity and potential for predicting ICP inhibitors (ICI) response have been described for only a few lncRNAs. Here we present an integrated framework that leverages network-based analyses and Bayesian network inference to identify the regulated relationships including lncRNA, ICP and immunity genes as ICP-related LncRNAs mediated Core Regulatory Circuitry Triplets (ICP-LncCRCTs) that can make robust predictions. Hub ICP-related lncRNAs such as MIR155HG and ADAMTS9-AS2 were highlighted to play central roles in immune regulation. Specific ICP-related lncRNAs could distinguish cancer subtypes. Moreover, the ICP-related lncRNAs are likely to significantly correlated with immune cell infiltration, MHC, CYT. Some ICP-LncCRCTs such as CXCL10-MIR155HG-ICOS could better predict one-, three- and five-year prognosis compared to single molecule in melanoma. We also validated that some ICP-LncCRCTs could effectively predict ICI-response using three kinds of machine learning algorithms follow five independent datasets. Specially, combining ICP-LncCRCTs with the tumor mutation burden (TMB) improves the prediction of ICI-treated melanoma patients. Altogether, this study will improve our grasp of lncRNA functions and accelerating discovery of lncRNA-based biomarkers in ICI treatment.

Clinicopathological characteristics and genomic profiling of pure mucinous breast cancer.

PURPOSE: Pure mucinous breast cancer (PMC) is a rare histological type with a favourable prognosis. However, cases with recurrence have been reported and diagnosed in clinical practice. The mechanisms underlying PMC recurrence remain unknown. In this study, we aimed to identify the prognostic factors associated with PMC. MATERIALS AND METHODS: A total of 166 patients diagnosed with PMC were included. We compared the clinicopathological characteristics between patients with and without recurrence. The 21-gene assay was performed in 10 patients with recurrence and 20 TNM stage-matched patients without recurrence. Whole-exon sequencing was performed in 12 PMC primary tumours and four positive lymph nodes (LNs). RESULTS: Tumour size, lymph node status and TNM staging differed significantly between recurrent group and non-recurrent group. And the 21-gene recurrence scores did not differ significantly between recurrent group and its TNM stage-matched non-recurrent group. The most frequently mutated genes in the primary tumours of regional LN-positive PMCs were ADCY10 (3/6) and SHANK3 (3/6), and they more recurrently harboured gains of 15q23, 17q23.2 and 20p11.21, and loss of 21p11.2. And these alterations were not detected in primary tumours of regional LN-negative PMCs. CONCLUSION: TNM stage is an important prognostic factor in PMC. Although we revealed that regional LN-positive PMCs show increased occurrence of duplication variants at 15q23, 17q23.2 and 20p11.21, and deletion variants at 21p11.2. Further investigation, including multi-omics studies, are needed and may provide additional insights into the nature of PMC.