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Conventional model-driven methods are hard to handle large-scale power flow with multivariate uncertainty, variable topology, and massive real-time repetitive calculations. With the ability to deal with non-Euclidean graph-structured power system data, graph deep learning shows great potential in modern power flow calculation. However, general graph deep learning based power flow calculation has limited adaptability because of its sole mapping of node information and black-box attributes. In this paper, an edge graph attention network based power flow calculation (EGAT-PFC) model is proposed with improved adaptability for power flow analysis of complex system scenarios. First, the dual-model structure of the node model and edge model is constructed to realize a complete power flow mapping covering all information in power systems. Second, an improved learnable attention coefficient mechanism fusing node and edge features is proposed to ensure global information can be completely considered. Third, mechanisms of extended first-order neighborhood, dynamic normalization, and regularization-based loss function are designed to improve training performance. Finally, visualized interpretability is developed to show valuable information of vulnerable nodes and lines of power system operation. The numerical simulation verifies that EGAT-PFC has high accuracy, fast mapping, as well as excellent adaptability to variable topologies.

Objective: This study aimed to assess the chemopreventive effect of ursodeoxycholic acid (UDCA) against COVID-19 and to analyze infection risk factors, symptoms, and recovery in outpatients with UDCA exposure.Methods: The study enrolled outpatients prescribed UDCA from the Second Affiliated Hospital of Chongqing Medical University, China, between 01 July 2022, and 31 December 2022. Data on demographics, comorbidities, and drug combinations were collected using electronic medical records. COVID-19 infection, symptoms, severity, prognosis, vaccinations, and UDCA administration were surveyed by telephone interviews. UDCA non-users served as controls and were matched in a 1:2 ratio with UDCA users using propensity score matching with the nearest neighbor algorithm. Infection rates, symptomatology, severity, and prognosis were compared between matched and control cohorts, and risk factors and infection and recovery symptoms were analyzed in UDCA-exposed outpatients.Results: UDCA-exposed outpatients (n = 778, 74.8%) and matched UDCA users (n = 95, 74.2%) showed significantly lower SARS-CoV-2 infection rates than control patients (n = 59, 92.2%) (p < 0.05). The matched UDCA group exhibited substantially lower fever, cough, sore throat, and fatigue rates than controls (p < 0.05). Participants with UDCA exposure generally experienced mild symptoms, while those without UDCA had moderate symptoms. The matched UDCA group also had significantly shorter durations of fever and cough (p < 0.05). Risk factors such as age over 60, less than 1 month of UDCA administration, diabetes mellitus, and coronary artery disease significantly increased SARS-CoV-2 infection rates (p < 0.05), while smoking led to a decrease (p < 0.05). Hypertension was associated with a prolonged COVID-19 recovery (p < 0.05), while smoking, vaccination, and fatty liver disease were associated with shorter recovery periods (p < 0.05). The main symptoms in the full UDCA cohort were fever, cough, and sore throat, with fatigue, cough, and hyposthenia being the most persistent.Conclusion: UDCA demonstrated chemopreventive effect against SARS-CoV-2 in outpatients by significantly reducing infection incidence and mitigating COVID-19 symptoms, severity, and recovery duration. Old age, short UDCA course, and comorbidities such as diabetes mellitus and CAD increased infection rates, while hypertension prolonged recovery. Smoking, vaccination, and fatty liver disease reduced infection rates and shortened recovery. UDCA had minimal impact on symptom types. Larger and longer-term clinical studies are needed further to assess UDCA’s effectiveness in COVID-19 prevention or treatment.

With the construction of new-type power system under the ”double carbon” target and the increasing diversification of the energy demand of the user side, the short-term load forecasting of power system is facing new challenges. In order to fully exploit the massive information contained in big data, this paper proposed a new short-term load forecasting method for new-type power system considering multiple factors, which based on Graph Convolutional Network (GCN) and Long Short-Term Memory network (LSTM). Spearman rank correlation coefficient was used to analyze the correlation between load and meteorological factors, and a quantitative model including meteorological factors, date factors and regional factors was established. Thus, GCN and LSTM were jointly used to extract the spatial and temporal characteristics of massive data respectively, and finally the short-term power load forecasting was achieved. The public data sets were used for performance verification compared with three comparison models, LSTM, CNN-LSTM and TCN-LSTM. The results show that the proposed method can make full use of the influence of multi-dimensional data, meanwhile improve the load prediction accuracy and training efficiency effectively.

Abstract Objectives The risk and beneficial factors of early discharge after thoracoscopic anatomic lung cancer surgery are unknown, and this study aims to investigate predictors and associated 30‐day readmission for early discharge. Methods We performed a single‐center retrospective analysis of 10,834 consecutive patients who underwent thoracoscopic anatomic lung cancer surgery. Two groups were determined based on discharge date: “discharged by postoperative Day 2” and “discharged after postoperative Day 2.” Univariable and multivariable analysis were conducted to identify predictors for discharge. Using propensity score matching (PSM) to compare 30‐day readmission rate between two cohorts. Results A total of 1911 patients were discharged by postoperative Day 2. Multivariable analysis identified older age (odds ratio (OR) = 1.014, p

Objective: Vitamin D3 has the general properties of a lipid-soluble vitamin, but is also an active steroid hormone that can regulate the proliferation, apoptosis and differentiation of many tumor cells, and exerts anticancer activity against numerous malignancies. However, the mechanism underlying the effects of vitamin D3 on tumors is not fully understood. Here, we used network pharmacology and in vitro experimental approaches to explore the mechanism of vitamin D3 activity in the context of gastric cancer.Methods: The Targetnet, SuperPred, SwissTargetPrediction, and PharmMapper databases were screened for potential drug-related targets, while we used data from the PharmGKB, Drugbank, OMIM, DisGeNET, CTD, and GeneCards databases to identify potential targets associated with gastric cancer. Disease-drug crossover genes were obtained by constructing Venn diagrams. Gene ontology and Kyoto Encyclopedia of Genomes (KEGG) enrichment analyses of crossover genes were conducted and STRING was used to generate protein interaction networks and identify core targets. CCK-8 experiments were performed and apoptosis detected to assess the effect of vitamin D3 on gastric cancer cells. Western blotting was applied to detect p53/AMPK/mTOR signaling, as well as autophagy-, cell cycle-, and apoptosis-related proteins.Results: A total of 485 targets of vitamin D3 activity were obtained and 1200 gastric cancer disease-related targets discovered. Further, 60 potential targets for vitamin D3 in gastric cancer treatment were identified. KEGG analysis indicated that potential targets were mainly involved in the cell cycle, HIF-1 signaling, and the AMPK pathway, among other pathways. These findings were validated using cellular experiments, which demonstrated that the viability of AGS and SGC-7901 cells was impeded by vitamin D3. Further, vitamin D3 promoted apoptosis and inhibited the cell cycle in those cell lines, as well as activating the p53/AMPK/mTOR pathway, which promotes autophagy and inhibits tumor development.Conclusion: Our network pharmacological analyses provide preliminarily data supporting a role for vitamin D3 in promoting autophagy and apoptosis in gastric cancer cells, and in activating the p53/AMPK/mTOR pathway, which inhibits gastric cancer cell proliferation. Our findings demonstrate the molecular mechanism underlying the effect of vitamin D3 in cure of gastric cancer.

This paper aims to provide a reduced-complexity decoding for satellite communication systems to enhance system performance and transmission efficiency. By addressing the complexity, error rate, and latency issues for satellite communications, a novel 3-dimensional product decoding scheme is proposed. The density evolution algorithm is also introduced to analyze and optimize for the binary message passing decoding, which further reduces the computational complexity and latency. The simulation results show that the proposed method can obtain about 0.3- and 0.15-dB performance gains compared to the similar decodings of the conventional 2-dimensional BCH product codes and staircase codes, respectively. Our proposed coding scheme offers a broad prospect to the critical issues of transmission latency and data throughput in satellite networks.

Objective: Aloe-emodin (AE) is an anthraquinone compound extracted from the rhizome of the natural plant rhubarb. Initially, it was shown that AE exerts an anti-inflammatory effect. Further studies revealed its antitumor activity against various types of cancer. However, the mechanisms underlying these properties remain unclear. Based on network pharmacology and molecular docking, this study investigated the molecular mechanism of AE in the treatment of hepatocellular carcinoma (HCC), and evaluated its therapeutic effect through in vitro experiments.Methods: CTD, Pharmmapper, SuperPred and TargetNet were the databases to obtain potential drug-related targets. DisGenet, GeneCards, OMIM and TTD were used to identify potential disease-related targets. Intersection genes for drugs and diseases were obtained through the Venn diagram. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of intersecting genes were conducted by the website of Bioinformatics. Intersection genes were introduced into STRING to construct a protein-protein interaction network, while the Cytoscape3.9.1 software was used to visualize and analyze the core targets. AutoDock4.2.6 was utilized to achieve molecular docking between drug and core targets. In vitro experiments investigated the therapeutic effects and related mechanisms of AE.Results: 63 overlapped genes were obtained and GO analysis generated 3,646 entries by these 63 intersecting genes. KEGG analysis mainly involved apoptosis, proteoglycans in cancer, TNF signaling pathway, TP53 signaling pathway, PI3K-AKT signaling pathway, etc. AKT1, EGFR, ESR1, TP53, and SRC have been identified as core targets because the binding energies of them between aloe-emodin were less than -5 kcal/Mol.The mRNA and protein expression, prognosis, mutation status, and immune infiltration related to core targets were further revealed. The involvement of AKT1 and EGFR, as well as the key target of the PI3K-AKT signaling pathway, indicated the importance of this signaling pathway in the treatment of HCC using AE. The results of the Cell Counting Kit-8 assay and flow analysis demonstrated the therapeutic effect of AE. The downregulation of EGFR, PI3KR1, AKT1, and BCL2 in mRNA expression and PI3KR1, AKT,p-AKT in protein expression confirmed our hypothesis.Conclusion: Based on network pharmacology and molecular docking, our study initially showed that AE exerted a therapeutic effect on HCC by modulating multiple signaling pathways. Various analyses confirmed the antiproliferative activity and pro-apoptotic effect of AE on HCC through the PI3K-AKT signaling pathway. This study revealed the therapeutic mechanism of AE in the treatment of HCC through a novel approach, providing a theoretical basis for the clinical application of AE.

Abstract Background Sleeve lobectomy is recognized as an alternative surgical operation to pneumonectomy because it preserves the most pulmonary function and has a considerable prognosis. In this study, we aimed to investigate the implications of residual status for patients after sleeve lobectomy. Methods In this retrospective cohort study, we summarized 58 242 patients who underwent surgeries from 2015 to 2018 in Shanghai Chest Hospital and found 456 eligible patients meeting the criteria. The status of R2 was excluded. The outcomes were overall survival (OS) and recurrence‐free survival (RFS). We performed a subgroup analysis to further our investigation. Results After the propensity score match, the baseline characteristic was balanced between two groups. The survival analysis showed no significant difference of overall survival and recurrence‐free survival between R0 and R1 groups (OS: p = 0.053; RFS: p = 0.14). In the multivariate Cox analysis, we found that the margin status was not a dependent risk factor to RFS (p = 0.119) and OS (p = 0.093). In the patients of R1, N stage and age were closely related to OS, but we did not find any significant risk variable in RFS for R1 status. In the subgroup analysis, R1 status may have a worse prognosis on patients with more lymph nodes examination. On further investigation, we demonstrated no differences among the four histological types of margin status. Conclusion In our study, we confirmed that the margin status after sleeve lobectomies was not the risk factor to prognosis. However, patients with more lymph nodes resection should pay attention to the margin status.

Objective: Colorectal cancer (CRC) is a common cancer that cannot be detected at an early stage and is a major challenge in oncology research. Studies have shown that vitamin D3 has some anti-cancer and preventive effects on colorectal cancer, but the exact anti-cancer mechanism is not clear. We applied the relevant research methods of network pharmacology to speculate and validate the possible potential pharmacological mechanisms of vitamin D3 for the prevention of colorectal cancer, and to provide more theoretical support for the clinical anticancer effects of vitamin D3.Methods: The relevant targets for vitamin D3 and CRC were obtained from the database of drug and disease targets, respectively. The target of vitamin D3 and the target of colorectal cancer were taken to intersect to obtain common targets. Then, the PPI network was constructed. In addition, the pathways of drug-disease interactions were predicted by GO and KEGG enrichment analysis. Finally, the obtained results were verified to ensure the reliability of the experiments.Results: 51 targets of vitamin D3 for the prevention of colorectal cancer were obtained. The 10 core targets were obtained from the PPI network. The 10 core targets include: ALB, SRC, MMP9, PPARG, HSP90AA1, IGF1, EGFR, MAPK1, MAP2K1 and IGF1R. The core targets were further validated by molecular docking and animal experiments. The results suggest that vitamin D3 plays a key role in the prevention of CRC through core targets, PI3K-Akt pathway, HIF-1 pathway, and FoxO pathway.Conclusion: This study will provide more theoretical support for vitamin D3 to reduce the incidence of CRC and is important to explore more pharmacological effects of vitamin D3.

Abstract There have been significant advancements in medical techniques in the present epoch, with the emergence of some novel operative substitutes. However, the treatment of tracheal defects still faces tremendous challenges and there is, as yet, no consensus on tracheal and carinal reconstruction. In addition, surgical outcomes vary in different individuals, which results in an ambiguous future for tracheal surgery. Although transplantation was once an effective and promising method, it is limited by a shortage of donors and immune rejection. The development of bioengineering has provided an alternative for the treatment of tracheal defects, but this discipline is full of ethical controversy and hindered by limited cognition in this area. Meanwhile, progression of this technique is blocked by a deficiency in ideal materials. The trachea together with the carina is still the last unpaired organ in thoracic surgery and propososal of a favorable scheme to remove this dilemma is urgently required. In this review, four main tracheal reconstruction methods, especially surgical techniques, are evaluated, and a thorough interpretation conducted.

A dynamic multi-symbol (DM) flipping scheme is proposed for various symbol flipping decodings of non-binary low-density parity-check (NB-LDPC) codes. This new approach divides the whole decoding process into multiple stages according to the number of iterations and allows a different maximum number of symbols to be flipped in each stage. Numerical analysis reveals that the proposed multi-symbol flipping scheme can yield a higher probability of correct flipping with the dynamic flipping threshold. The proposed DM scheme can be highly parallelized, extensively improving the decoder throughput over existing symbol flipping decoding algorithms based on prediction (SFDP). Numerical results show that the DM scheme can significantly enhance the error correction capability and achieve faster convergence speed with little increase in average computational complexity.

Objective: Curcumin is a plant polyphenol extracted from the Chinese herb turmeric. It was found that curcumin has good anti-cancer properties in a variety of cancers, but the exact mechanism is not clear. Based on the network pharmacology and molecular docking to deeply investigate the molecular mechanism of curcumin for the treatment of colon cancer, it provides a new research direction for the treatment of colon cancer.Methods: Curcumin-related targets were collected using PharmMapper, SwissTargetPrediction, Targetnet and SuperPred. Colon cancer related targets were obtained using OMIM, DisGeNET, GeneCards and GEO databases. Drug-disease intersection targets were obtained via Venny 2.1.0. GO and KEGG enrichment analysis of drug-disease common targets were performed using DAVID. Construct PPI network graphs of intersecting targets using STRING database as well as Cytoscape 3.9.0 and filter core targets. Molecular docking via AutoDockTools 1.5.7. The core targets were further analyzed by GEPIA, HPA, cBioPortal and TIMER databases.Results: A total of 73 potential targets of curcumin for the treatment of colon cancer were obtained. GO function enrichment analysis yielded 256 entries, including BP(Biological Progress):166, CC(celluar component):36 and MF(Molecular Function):54. The KEGG pathway enrichment analysis yielded 34 signaling pathways, mainly involved in Metabolic pathways, Nucleotide metabolism, Nitrogen metabolism, Drug metabolism - other enzymes, Pathways in cancer,PI3K-Akt signaling pathway, etc. CDK2, HSP90AA1, AURKB, CCNA2, TYMS, CHEK1, AURKA, DNMT1, TOP2A, and TK1 were identified as core targets by Cytoscape 3.9.0. Molecular docking results showed that the binding energies of curcumin to the core targets were all less than 0 kJ-mol-1, suggesting that curcumin binds spontaneously to the core targets. These results were further validated in terms of mRNA expression levels, protein expression levels and immune infiltration.Conclusion: Based on network pharmacology and molecular docking initially revealed that curcumin exerts its therapeutic effects on colon cancer with multi-target, multi-pathway. Curcumin may exert anticancer effects by binding to core targets. Curcumin may interfere with colon cancer cell proliferation and apoptosis by regulating signal transduction pathways such as PI3K-Akt signaling pathway,IL-17 signaling pathway, Cell cycle. This will deepen and enrich our understanding of the potential mechanism of curcumin against colon cancer and provide a theoretical basis for subsequent studies.

With the construction of a new-type power system under the China “double carbon” target and the increasing diversification of the energy demand on the user side, the short-term load forecasting of the power system is facing new challenges. To fully exploit the massive information contained in data, based on the graph convolutional network (GCN) and long short-term memory network (LSTM), this paper presents a new short-term load forecasting method for power systems considering multiple factors. The Spearman rank correlation coefficient was used to analyse the correlation between load and meteorological factors, and a model including meteorology, dates, and regions was established. Secondly, GCN and LSTM are jointly used to extract the spatial and temporal characteristics of massive data, respectively, and finally achieve short-term power load prediction. Historical electrical load data from 2020 to 2022 public data of a real industrial park in southern China were selected to verify the validity of the proposed method from the aspects of forecasting accuracy, feature dimension, and training time.

Myocardial remodeling is a key pathophysiological basis of heart failure, which seriously threatens human health and causes a severe economic burden worldwide. During chronic stress, the heart undergoes myocardial remodeling, mainly manifested by cardiomyocyte hypertrophy, apoptosis, interstitial fibrosis, chamber enlargement, and cardiac dysfunction. The NADPH oxidase family (NOXs) are multisubunit transmembrane enzyme complexes involved in the generation of redox signals. Studies have shown that NOXs are highly expressed in the heart and are involved in the pathological development process of myocardial remodeling, which influences the development of heart failure. This review summarizes the progress of research on the pathophysiological processes related to the regulation of myocardial remodeling by NOXs, suggesting that NOXs-dependent regulatory mechanisms of myocardial remodeling are promising new therapeutic targets for the treatment of heart failure.

Abstract Background The BOLA gene family, comprising three members, is mainly involved in regulating intracellular iron homeostasis. Emerging evidence suggests that BolA family member 2 plays a vital role in tumorigenesis and hepatic cellular carcinoma progression. However, there was less known about its role in ovarian cancer. Methods In the present study, we investigated the expression profiles, prognostic roles, and genetic alterations of three BolA family members in patients with ovarian cancer through several public databases, containing Oncomine and Gene Expression Profiling Interactive Analysis, Human Protein Atlas, Kaplan–Meier plotter and cBioPortal. Then, we constructed the protein-protein interaction networks of BOLA proteins and their interactors by using the String database and Cytoscape software. In addition, we performed the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment by the Annotation, Visualization, and Integrated Discovery database. Finally, we explored the mechanisms underlying BolA family members’ involvement in OC by using gene set enrichment analysis. Results The mRNA and protein expression levels of BOLA2 and BOLA3 were heavily higher in ovarian cancer tissues than in normal ovarian tissues. Dysregulated mRNA expressions of three BolA family members were significantly associated with prognosis in overall or subgroup analysis. Moreover, genetic alterations also occurred in three BolA family members in ovarian cancer. GO analysis indicated that BolA family members might regulate the function of metal ion binding and protein disulfide oxidoreductase activity. Gene set enrichment analysis indicated that BolA family members were mainly associated with oxidative phosphorylation, proteasome, protein export, and glutathione metabolism in ovarian cancer. Conclusion In brief, our finding may contribute to increasing currently limited prognostic biomarkers and treatment options for ovarian cancer.

Although long polar codes with successive cancellation decoding can asymptotically achieve channel capacity, the performance of short blocklength polar codes is far from optimal. Recently, Arıkan proposed employing a convolutional pre-transformation before the polarization network, called polarization-adjusted convolutional (PAC) codes. In this paper, we focus on improving the performance of short PAC codes concatenated with a cyclic redundancy check (CRC) outer code, CRC-PAC codes, since error detection capability is essential in practical applications, such as the polar coding scheme for the control channel. We propose an enhanced adaptive belief propagation (ABP) decoding algorithm with the assistance of CRC bits for PAC codes. We also derive joint parity-check matrices of CRC-PAC codes suitable for iterative BP decoding. The proposed CRC-aided ABP (CA-ABP) decoding can effectively improve error performance when partial CRC bits are used in the decoding. Meanwhile, the error detection ability can still be guaranteed by the remaining CRC bits and adaptive decoding parameters. Moreover, compared with the conventional CRC-aided list (CA-List) decoding, our proposed scheme can significantly reduce computational complexity, to achieve a better trade-off between the performance and complexity for short PAC codes.

Although metastasis of clear cell renal cell carcinoma (ccRCC) is basically observed in late stage tumors, T1 stage metastasis of ccRCC can also be found with no definite molecular cause resulting inappropriate selection of surgery method and poor prognosis. Notch signaling is a conserved, widely expressed signal pathway that mediates various cellular processes in normal development and tumorigenesis. This study aims to explore the potential role and mechanism of Notch signaling in the metastasis of T1 stage ccRCC.The expression of Notch1 and Jagged1 were analyzed in tumor tissues and matched normal adjacent tissues obtained from 51 ccRCC patients. Compared to non-tumor tissues, Notch1 and Jagged1 expression was significantly elevated both in mRNA and protein levels in tumors. Tissue samples of localized and metastatic tumors were divided into three groups based on their tumor stages and the relative mRNA expression of Notch1 and Jagged1 were analyzed. Compared to localized tumors, Notch1 expression was significantly elevated in metastatic tumors in T1 stage while Jagged1 expression was not statistically different between localized and metastatic tumors of all stages. The average size of metastatic tumors was significantly larger than localized tumors in T1 stage ccRCC and the elevated expression of Notch1 was significantly positive correlated with the tumor diameter. The functional significance of Notch signaling was studied by transfection of 786-O, Caki-1 and HKC cell lines with full-length expression plasmids of Notch1 and Jagged1. Compared to the corresponding controls, all cell lines demonstrated significant promotion in cell proliferation and migration while cell cycle remained unaffected.High-level expression of Notch signaling increased the risk of metastasis in T1 stage ccRCC by stimulating the proliferation and migration of tumor cells, which may be helpful for the selection of suitable operation method and prognosis of ccRCC.