FSCME: A Feature Selection Method Combining Copula Correlation and Maximal Information Coefficient by Entropy Weights.

Feature selection is a critical component of data mining and has garnered significant attention in recent years. However, feature selection methods based on information entropy often introduce complex mutual information forms to measure features, leading to increased redundancy and potential errors. To address this issue, we propose FSCME, a feature selection method combining Copula correlation (Ccor) and the maximum information coefficient (MIC) by entropy weights. The FSCME takes into consideration the relevance between features and labels, as well as the redundancy among candidate features and selected features. Therefore, the FSCME utilizes Ccor to measure the redundancy between features, while also estimating the relevance between features and labels. Meanwhile, the FSCME employs MIC to enhance the credibility of the correlation between features and labels. Moreover, this study employs the Entropy Weight Method (EWM) to evaluate and assign weights to the Ccor and MIC. The experimental results demonstrate that FSCME yields a more effective feature subset for subsequent clustering processes, significantly improving the classification performance compared to the other six feature selection methods. The source codes of the FSCME are available online at https://github.com/CDMBlab/FSCME.

Breaking barriers: How modified citrus pectin inhibits galectin-8.

Inhibition of galectin-3-mediated interactions by modified citrus pectin (MCP) could affect several rate-limiting steps in cancer metastasis, but the ability of MCP to antagonize galectin-8 function remains unknown. We hypothesized that MCP could bind to galectin-8 in addition to galectin-3. In this study, a combination of gradual ethanol precipitation and DEAE-Sepharose Fast Flow chromatography was used to isolate several fractions from MCP. The ability of these fractions to antagonize galectin-8 function was studied as well as the primary structure and initial structure-function relationship of the major active component MCP-30-3. The results showed that MCP-30-3 (168 kDa) was composed of Gal (13.8%), GalA (63.1%), GlcA (13.0%), and Glc (10.1%). MCP-30-3 could specifically bind to galectin-8, with an MIC value of 0.04 mg mL-1. After MCP-30-3 was hydrolyzed by ß-galactosidase or pectinase, its binding activity was significantly reduced. These results provide new insights into the interaction between MCP structure and galectin function, as well as the potential utility in the development of functional foods.

Exploring the effects of calycosin on anthracycline-induced cardiotoxicity: a network pharmacology, molecular docking, and experimental study.

Background: Chemotherapy with anthracyclines can cause cardiotoxicity, possibly leading to stopping treatment in some cancer patients. In cardio-oncology research, preventing and minimizing anthracycline-induced cardiotoxicity (AIC) is a hot issue. For the treatment of AIC, calycosin (CA), an isoflavone component in astragali radix (AR), has become a research focus. However, the elaborate mechanisms of calycosin treating AIC remain to be unrevealed. Aim of the study: To explore the effects of CA on AIC through multiple dimensions concerning network pharmacology, molecular docking, and experimental evaluations. Methods: The study evaluated calycosin's potential targets and mechanisms for treating AIC using network pharmacology and molecular docking. The candidate genes/targets of CA and AIC were screened using the online-available database. Protein-protein interactions (PPI) between the common targets were constructed using the STRING platform, and the results were then visualized using Cytoscape. Molecular docking was used to evaluate the strength of the binding force between CA and the common targets. The possible pharmacological mechanisms of CA were explained by pathway enrichment and GSEA. Subsequently, the candidate targets were identified in vitro experiments. Results: Network pharmacology effectively discovered the CA's multitarget intervention in AIC, including TNF, ABCC1, TOP2A, ABCB1, and XDH. CA binds to the ATP-binding cassette subfamily B member 1(ABCB1) had the highest binding energy (-7.5 kcal/mol) according to the molecular docking analysis and was selected and visualized for subsequent analysis. In vitro experiments showed that ABCB1 exhibited significant time-curve changes under different doses of doxorubicin (DOX) compared with DMSO control experiments. The anti-AIC pharmacological mechanism of CA were revealed by highlighting the biological processes of oxidative stress (OR) and inflammation. Conclusions: We employed a practicable bioinformatics method to connect network and molecular docking to determine the calycosin's therapeutic mechanism against AIC and identified some bioinformatics results in in vitro experiments. The results presented show that CA may represent an encouraging treatment for AIC.

Anti-inflammatory activities of several diterpenoids isolated from Hemionitis albofusca.

Hemionitis albofusca (Baker) Christenh is a plant that grows in various regions of China. Although it is not recognized as a traditional medicine, it is often mistakenly labelled and used as Aleuritopteris argentea (S. G. Gmél.) Fée to alleviate menstruation-related issues. Recently, several diterpenoids such as ent-16-oxo-17-norkauran-19-oic acid (Compound A), 14-oxy-7ß,20-dihydroxycyath-12,18-diene (Compound B), ent-8(14),15-pimaradiene-2ß,19-diol (Compound C), ent-kaurane-16-ene-2ß,18α-diol (Compound D), ent-kaurane-2ß,16α,18α-triol (Compound E), and onychiol B have been extracted from H. albofusca. In this study, we investigated the anti-inflammatory activity of these diterpenes. We confirmed that compounds A ~ D suppressed the amount of cellular NO production by inhibiting the expression and transcription of iNOS protein. They also significantly inhibited the expression and transcription of inflammatory factors TNF-α and IL-6. Additionally, Compounds A and C suppressed the activation of the NF-κB signaling pathway and inhibited the phosphorylation level of p38, ultimately down-regulating inflammation. Compound B suppressed the activation of the NF-κB signaling pathway, while Compound D inhibited the phosphorylation level of p38 and down-regulated the activation of the p38 MAPK signaling pathway. In a word, our investigation supports the potential application of natural diterpenes as lead compounds for developing anti-inflammatory agents.

A clean and efficient route for extraction of vanadium from vanadium slag by electro-oxidation combined with ultrasound cavitation.

Extracting vanadium (V) from vanadium slag (VS) by the traditional roasting-leaching process has disadvantages of high energy consumption and high poisonous gases emission. In this work, a green and efficient route was developed to extract V from VS without roasting by electro-oxidation combined with ultrasound cavitation (EOUC) intensification in sulfuric acid solution. The leaching parameters (e.g., leaching temperature, sulfuric acid concentration, anodic current density, ultrasound power, liquid to solid ratio, leaching time and particle size) were optimized. The leaching mechanism was explored by comparing the leaching behavior and mineralogical evolution of the direct sulfuric acidic leaching (DSL), electro-oxidation-assisted sulfuric acidic leaching (EOSL), ultrasound cavitation-assisted sulfuric acidic leaching (UCSL) and EOUC methods. The results show that introducing electric field strengthens the ultrasound cavitation effect on slag particles in sulfuric acid solution. Under the optimum parameter of EOUC method, the leaching rate of V from VS is as high as 94.64 %. Using EOUC method can open the silicate-wrapped structure of the spinel, increase pore volume of VS from 0.00127 cm3 g-1 to 0.01124 cm3 g-1, decrease slag particle size from 26.8 µm to 16.4 µm and improve specific surface area from 0.508 m2 g-1 to 10.855 m2 g-1, which significantly accelerate V leaching process. The exposed spinel was oxidized by both electrochemical route and chemical route, forming a mixture of V3+ ion and VO2+ ion after leaching.

Psychological capital among clinical nurses: A latent profile analysis.

AIM: To determine the psychological capital level of nurses and explore the latent profiles of nurses regarding their psychological capital scores. BACKGROUND: The use of individual-centered analysis for the connotation of nurses' psychological capital structure is less studied and still needs to be further explored. METHODS: By the convenience sampling method, 494 clinical nurses from 7 general hospitals in Sichuan province were selected. The study was conducted from December 2022 to February 2023. Latent profile analysis was used for data analysis. We followed STROBE guidelines in this research. RESULTS: The total mean score of nurses' psychological capital is 5.17 (SD = 0.8). The following four latent profiles were identified: "poor" (4.5%), "medium" (22.9%), "well-off" (41.5%), and "rich" (31.1%). Multiple logistic regression showed that the number of hours worked per day and the number of night shifts per month were negative predictors of psychological capital, and psychological training and job satisfaction were protective factors of psychological capital. DISCUSSION: Our study found that the four profiles can be distinguished by "poor," "well-off," "medium," and "rich" levels of psychological capital. Among them, more than 70% of the nurses belonged to the well-off and rich profiles, and the number of the poor profile was the lowest. CONCLUSION: The overall psychological capital of clinical nurses is at a medium-high level. Each profile is influenced by multiple sociodemographic factors (i.e., age, working hours, monthly income, psychological training, and job satisfaction). IMPLICATIONS FOR NURSING AND HEALTH POLICY: Administrators should develop enhancement strategies to improve the mental health of nurses based on the characteristics of their psychological capital profiles.

Efficient FMT reconstruction based on L1-αL2 regularization via half-quadratic splitting and a two-probe separation light source strategy.

Fluorescence molecular tomography (FMT) can achieve noninvasive, high-contrast, high-sensitivity three-dimensional imaging in vivo by relying on a variety of fluorescent molecular probes, and has excellent clinical transformation prospects in the detection of tumors in vivo. However, the limited surface fluorescence makes the FMT reconstruction have some ill-posedness, and it is difficult to obtain the ideal reconstruction effect. In this paper, two different emission fluorescent probes and L 1-L 2 regularization are combined to improve the temporal and spatial resolution of FMT visual reconstruction by introducing the weighting factor α and a half-quadratic splitting alternating optimization (HQSAO) iterative algorithm. By introducing an auxiliary variable, the HQSAO method breaks the sparse FMT reconstruction task into two subproblems that can be solved in turn: simple reconstruction and image denoising. The weight factor α (α>1) can increase the weight of nonconvex terms to further promote the sparsity of the algorithm. Importantly, this paper combines two different dominant fluorescent probes to achieve high-quality reconstruction of dual light sources. The performance of the proposed reconstruction strategy was evaluated by digital mouse and nude mouse single/dual light source models. The simulation results show that the HQSAO iterative algorithm can achieve more excellent positioning accuracy and morphology distribution in a shorter time. In vivo experiments also further prove that the HQSAO algorithm has advantages in light source information preservation and artifact suppression. In particular, the introduction of two main emission fluorescent probes makes it easy to separate and reconstruct the dual light sources. When it comes to localization and three-dimensional morphology, the results of the reconstruction are much better than those using a fluorescent probe, which further facilitates the clinical transformation of FMT.

Chemical Modification of Polysaccharides: A Review of Synthetic Approaches, Biological Activity and the Structure-Activity Relationship.

Natural polysaccharides are macromolecular substances with great potential owing to their wide biological activity and low toxicity. However, not all polysaccharides have significant pharmacodynamic activity; hence, appropriate chemical modification methods can be selected according to the unique structural characteristics of polysaccharides to assist in enhancing and promoting the presentation of their biological activities. This review summarizes research progress on modified polysaccharides, including common chemical modification methods, the change in biological activity following modification, and the factors affecting the biological activity of chemically modified polysaccharides. At the same time, the difficulties and challenges associated with the structural modification of natural polysaccharides are also outlined in this review. Thus, research on polysaccharide structure modification is critical for improving the development and utilization of sugar products.

iLncDA-RSN: identification of lncRNA-disease associations based on reliable similarity networks.

Identification of disease-associated long non-coding RNAs (lncRNAs) is crucial for unveiling the underlying genetic mechanisms of complex diseases. Multiple types of similarity networks of lncRNAs (or diseases) can complementary and comprehensively characterize their similarities. Hence, in this study, we presented a computational model iLncDA-RSN based on reliable similarity networks for identifying potential lncRNA-disease associations (LDAs). Specifically, for constructing reliable similarity networks of lncRNAs and diseases, miRNA heuristic information with lncRNAs and diseases is firstly introduced to construct their respective Jaccard similarity networks; then Gaussian interaction profile (GIP) kernel similarity networks and Jaccard similarity networks of lncRNAs and diseases are provided based on the lncRNA-disease association network; a random walk with restart strategy is finally applied on Jaccard similarity networks, GIP kernel similarity networks, as well as lncRNA functional similarity network and disease semantic similarity network to construct reliable similarity networks. Depending on the lncRNA-disease association network and the reliable similarity networks, feature vectors of lncRNA-disease pairs are integrated from lncRNA and disease perspectives respectively, and then dimensionality reduced by the elastic net. Two random forests are at last used together on different lncRNA-disease association feature sets to identify potential LDAs. The iLncDA-RSN is evaluated by five-fold cross-validation to analyse its prediction performance, results of which show that the iLncDA-RSN outperforms the compared models. Furthermore, case studies of different complex diseases demonstrate the effectiveness of the iLncDA-RSN in identifying potential LDAs.

Treatment of infected placenta accreta in the uterine horn by transabdominal temporary occlusion of internal iliac arteries: A case report and literature review.

RATIONALE: This case report aims to describe the treatment of infected placenta accreta in the uterine horn by transabdominal temporary occlusion of internal iliac arteries. PATIENT CONCERNS: A 29-year-old female patient had a history of retained placenta for 28 days after labor induction in the second trimester of pregnancy because of fetal malformation. DIAGNOSES: Placenta accreta in the uterine horn was diagnosed by 3-dimensional ultrasound and magnetic resonance imaging, and the diagnosis was confirmed during the operation. INTERVENTIONS: Laparotomy was performed to remove the placenta and repair the uterine defect after temporary occlusion of both internal iliac arteries. OUTCOMES: Body temperature and inflammatory markers were elevated at admission but returned to normal on the second day after surgery. Normal menstruation resumed approximately 1 month postoperatively. Ultrasound examination showed that the shape of the uterine cavity was normal. No postoperative complications were observed. LESSONS: Temporary occlusion of the internal iliac artery can help effectively manage infected placenta accreta in the uterine horn.

SCARB1 in extracellular vesicles promotes NPC metastasis by co-regulating M1 and M2 macrophage function.

Distant metastasis is currently the main factor affecting the prognosis of nasopharyngeal carcinoma (NPC), and understanding the mechanisms of metastasis and identifying reliable therapeutic targets are critical for improving prognosis and achieving clinical translation. Macrophages, as important immune cells in the tumor microenvironment (TME), have been shown to regulate metastasis. And extracellular vesicles (EVs) secreted by stromal cells and tumor cells play the important role in intercellular communication in the tumor microenvironment. However, the role of NPC-EVs on macrophages and their function in regulating macrophages to affect metastasis has not been fully clarified. In this study, we report that NPC-EVs can be uptake by macrophages and alter macrophage polarization, for the first time, we identified the genes implicated in these regulatory functions: SCARB1, HAAO, and CYP1B1. Moreover, we found that SCARB1 was positively associated with metastasis and poor prognosis of NPC. Interestingly, we found that SCARB1-rich EVs promoted M1 macrophages ferroptosis to decrease M1 macrophages infiltration by upregulating the HAAO level while decreasing phagocytosis of M2 macrophages by upregulating the CYP1B1 level. Finally, we identified the SCARB1-binding gene KLF9, which is involved in the transcription of HAAO and CYP1B1. Our findings showed that SCARB1-EVs promoted metastasis by co-regulating M1 and M2 macrophage function. The related mechanism will provide a new therapeutic strategy to help patients with NPC improve their prognosis.

GCCN: Graph Capsule Convolutional Network for Progressive Mild Cognitive Impairment Prediction and Pathogenesis Identification Based on Imaging Genetic Data.

In this study, we proposed a novel method called the graph capsule convolutional network (GCCN) to predict the progression from mild cognitive impairment to dementia and identify its pathogenesis. First, we proposed a novel risk gene discovery component to indirectly target genes with higher interactions with others. These risk genes and brain regions were collected as nodes to construct heterogeneous pathogenic information association graphs. Second, the graph capsules were established by projecting heterogeneous pathogenic information into a set of disentangled latent components. The orientation and length of capsules are representations of the format and intensity of pathogenic information. Third, graph capsule convolution network was used to model the information flows among pathogenic factors and elaborates the convergence of primary capsules to advanced capsules. The advanced capsule is a concept that organizes pathogenic information based on its consistency, and the synergistic effects of advanced capsules directed the development of the disease. Finally, discriminative pathogenic information flows were captured by a straightforward built-in interpretation mechanism, i.e., the dynamic routing mechanism, and applied to the identification of pathogenesis. GCCN has been experimentally shown to be significantly advanced on public datasets. Further experiments have shown that the pathogenic factors identified by GCCN are evidential and closely related to progressive mild cognitive impairment.

Heterozygous Pathogenic and Likely Pathogenic Symptomatic HTRA1 Variant Carriers in Cerebral Small Vessel Disease.

High temperature requirement serine peptidase A1 (HTRA1) related cerebral small vessel disease (CSVD) includes both symptomatic heterozygous HTRA1 variant carrier and cerebral autosomal recessive arteriopathy with subcortical infarcts and leukoencephalopathy (CARASIL) patients. Presently, most reported symptomatic heterozygous HTRA1 variant carrier cases are sporadic family reports with a lack of specific characteristics. Additionally, the molecular mechanism of heterozygous HTRA1 gene variants is unclear. We conducted this review to collect symptomatic carriers of heterozygous HTRA1 gene variants reported as of 2022, analyzed all pathogenicity according to American College of Medical Genetics and Genomics (ACMG) variant classification, and summarized the cases with pathogenic and likely pathogenic HTRA1 variants gender characteristics, age of onset, geographical distribution, initial symptoms, clinical manifestations, imaging signs, HTRA1 gene variant information and to speculate its underlying pathogenic mechanisms. In this review, we summarized the following characteristics of pathogenic and likely pathogenic symptomatic HTRA1 variant carriers: to date, the majority of reported symptomatic HTRA1 carriers are in European and Asian countries, particularly in China which was found to have the highest number of reported cases. The age of first onset is mostly concentrated in the fourth and fifth decades. The heterozygous HTRA1 gene variants were mostly missense variants. The two variant sites, 166-182 aa and 274-302 aa, were the most concentrated. Clinicians need to pay attention to de novo data and functional data, which may affect the pathogenicity analysis. The decrease in HtrA1 protease activity is currently the most important explanation for the genetic pathogenesis.

Contrast-enhanced CT parameters predict short-term tumor response in patients with hepatocellular carcinoma who received sequential combined anti-angiogenesis and immune checkpoint inhibitor treatment.

PURPOSE: To evaluate whether relative Hounsfield unit attenuation index (rHUAI) on contrast-enhanced computed tomography (CECT) can predict tumor response in advanced hepatocellular carcinoma (HCC) patients who received sequential combined treatment of immune checkpoint inhibitor (ICI) and anti-angiogenesis therapy. METHOD: One hundred seventeen advanced HCC patients who underwent the sequential combined treatment in a tertiary hospital between March 2020 and December 2021 were allocated to prediction and validation cohorts (with a ratio of 2:1) based on the time of initial ICI treatment. rHUAI from the arterial to the portal-venous phase (rHU_ap) and from the portal-venous to the delayed phase (rHU_pd) was calculated. The optimal cut-off values (COVs) of rHU_ap and rHU_pd for predicting tumor response were identified using Youden's index. Univariate and multivariable analyses were performed to assess the relationship between the COVs and tumor response. The validity of COVs was verified in the validation cohort using the chi-square test and Cramer's V coefficient (V). RESULTS: The optimal COVs of the two observers were 0.5316 and 0.3265 for rHU_ap, and -0.0208 and -0.0048 for rHU_pd, respectively. Multivariable analysis suggested that the COVs were independently associated with tumor response in the prediction cohort (rHU_ap, Odds ratio: 7.727 and 7.808, 95 % CI: 2.516-23.728 and 2.399-25.410, p value < 0.001 and 0.001; rHU_pd, Odds ratio: 0.034 and 0.011, 95 % CI: 0.002-0.600 and 0.001-0.209, p value of 0.021 and 0.003). In the validation cohort, the optimal COVs of rHU_ap had a moderate to a strong association with tumor response (V = 0.362-0.545, p < 0.05). The association between COVs of rHU_pd and tumor response was slight to strong (V = 0.24-0.545, p = 0.001 to 0.134). CONCLUSION: rHUAI obtained from CECT has the potential as a non-invasive tool for predicting tumor response in advanced HCC patients who have received combined ICI and anti-angiogenesis treatment.

MCFN: A Multichannel Fusion Network for Sleep Apnea Syndrome Detection.

Sleep apnea syndrome (SAS) is the most common sleep disorder which affects human life and health. Many researchers use deep learning methods to automatically learn the features of physiological signals. However, these methods ignore the different effects of multichannel features from various physiological signals. To solve this problem, we propose a multichannel fusion network (MCFN), which learns the multilevel features through a convolution neural network on different respiratory signals and then reconstructs the relationship between feature channels with an attention mechanism. MCFN effectively fuses the multichannel features to improve the SAS detection performance. We conducted experiments on the Multi-Ethnic Study of Atherosclerosis (MESA) dataset, consisting of 2056 subjects. The experiment results show that our proposed network achieves an overall accuracy of 87.3%, which is better than other SAS detection methods and can better assist sleep experts in diagnosing sleep disorders.

Three-in-one customized bioink for islet organoid: GelMA/ECM/PRP orchestrate pro-angiogenic and immunoregulatory function.

Islet organoids open up new strategies for diabetes treatment and pancreatic tissue engineering. Digital light processing (DLP) bioprinting has been extensively applied to the construction of organoids due to its ability to provide precisely patterned scaffolds with fast printing time while specific tailored bioink is indispensable for islet organoid. Customized bioinks that meet different needs were created and frequently applied based on gelatin methacryloyl (GelMA) mixed with other ingredients. Decellularized extracellular matrix (ECM) retains many organic specific structural and functional components and is widespread utilized to reconstruct the native niche like environment. However, considerable cytokines and growth factors were inevitably lost during the decellularized process, while platelet rich plasma (PRP) contains a string of growth factors which often exerted pro-angiogenic role. Therefore, a customized specific bioink for constructing islet organoid based on GelMA, pancreatic ECM and PRP was prepared in our research. In vitro, tube formation assay, CD31 immunofluorescence and relative mRNA expression of vascular genes indicated that the bioink with distinctively promote angiogenesis potential. Macrophages polarization was also conducted, which exhibited superior expression of CD206 (M2 marker) and inferior expression of iNOS (M1 marker). 3D printed organoids maintain the activity of mouse islet ß-cells (MIN6) with enhanced glucose sensitivity. In vivo, the results of CD31, CD206 and iNOS immunofluorescence were consistent with that in vitro. In summary, we prepared and characterized specific custom-made bioink with orchestrating immune-regulation response indicated by abundant M2-polarized macrophages, attenuated inflammation, and promoted angiogenesis, which provides an underlying bioink for the fabrication of 3D printed islet organoid.

Pylorus-preserving versus Pylorus-resecting: Impact on dynamic changes of nutrition and body composition in pancreatic cancer patients before and after pancreatoduodenectomy.

OBJECTIVES: To investigate if different methods of pancreatoduodenectomy (with or without pyloric preservation) would have different impacts on postoperative nutrition and body composition changes among pancreatic cancer patients. METHODS: Demographic and clinicopathological data, perioperative data were collected, body composition (e.g. skeletal muscle cross-sectional area [CSA], visceral fat area [VFA]) were evaluated with abdominal CT before and after surgery. Sarcopenia patients' proportion changes were also recorded. RESULTS: The hospital stay in the PRPD group was significantly less than that in the PPPD group (p < 0.05). A significant difference was found in CSA, skeletal muscle index (SMI), VFA, VFA/CSA and albumin (ALB) in both groups between preoperative, 3, and 12 months after surgery. The loss of visceral fat in the PRPD group was more prominent than that in the PPPD group at 3 months and 12 months after surgery (p < 0.05). VFA/CSA was higher in the PPPD group than in the PRPD group (3 months: p < 0.05, 12 months: p < 0.001). The proportion of sarcopenic patients increased significantly over time in the PPPD and PRPD groups (p < 0.001). CONCLUSIONS: Postoperative CSA and VFA continued to significantly decrease in both PPPD and PRPD groups, while the incidence of sarcopenia continued to increase. Compared with PRPD, PPPD has a protective effect on visceral fat. PPPD may contribute to better maintaining visceral fat mass and blood ALB levels. CT quantification can be an objective and effective method to evaluate the nutritional status of pancreatic cancer patients during the pre- and postoperative period and can provide a useful objective basis for guiding clinical treatment.

MDSN: A Module Detection Method for Identifying High-Order Epistatic Interactions.

Epistatic interactions are referred to as SNPs (single nucleotide polymorphisms) that affect disease development and trait expression nonlinearly, and hence identifying epistatic interactions plays a great role in explaining the pathogenesis and genetic heterogeneity of complex diseases. Many methods have been proposed for epistasis detection; nevertheless, they mainly focus on low-order epistatic interactions, two-order or three-order for instance, and often ignore high-order interactions due to computational burden. In this paper, a module detection method called MDSN is proposed for identifying high-order epistatic interactions. First, an SNP network is constructed by a construction strategy of interaction complementary, which consists of low-order SNP interactions that can be obtained from fast computations. Then, a node evaluation measure that integrates multi-topological features is proposed to improve the node expansion algorithm, where the importance of a node is comprehensively evaluated by the topological characteristics of the neighborhood. Finally, modules are detected in the constructed SNP network, which have high-order epistatic interactions associated with the disease. The MDSN was compared with four state-of-the-art methods on simulation datasets and a real Age-related Macular Degeneration dataset. The results demonstrate that MDSN has higher performance on detecting high-order interactions.

EBV promotes vascular mimicry of dormant cancer cells by potentiating stemness and EMT.

Vascular mimicry (VM) is defined as a vascular channel-like structure composed of tumor cells that correlates with the growth of cancer cells by providing blood circulation. However, whether VM can be formed in dormant cancer cells remains unclear. Our previous research revealed that polyploid giant cancer cells (PGCCs) are specific dormant cells related to the poor prognosis of head and neck cancer. Here, we demonstrated that EBV could promote VM formation by PGCCs in vivo and in vitro. Furthermore, we revealed that the activation of the ERK pathway partly mediated by LMP2A is responsible for stemness, and the acquisition of the stemness phenotype is crucial to the malignant biological behavior of PGCCs. The epithelial-to-mesenchymal transition (EMT) process plays a considerable role in PGCCs, and EMT progression is vital for EBV-positive PGCCs to form VM. This is the first study to reveal that EBV creates plasticity in PGCC-VM and provide a new strategy for targeted anti-tumor therapy.

Bta-miR-199a-3p Inhibits LPS-Induced Inflammation in Bovine Mammary Epithelial Cells via the PI3K/AKT/NF-κB Signaling Pathway.

Mastitis is characterized by inflammatory damage to mammary gland tissue, which could decline milk production and quality and significantly affect the economic benefits of ranching. MicroRNAs (miRNAs), such as miR-199a-3p, are novel therapeutic targets in inflammation, and their regulation is an effective strategy for inflammation control. Despite its importance in humans and animals, the molecular mechanism of bovine miR-199a-3p (bta-miR-199a-3p) in dairy cow mastitis and bovine mammary epithelial cell (bMEC) inflammation is unclear. In our study, a bovine mammary epithelial cell line (MAC-T) induced by lipopolysaccharide (LPS) was used as an inflammatory cell model to investigate the molecular mechanism of bta-miR-199a-3p in the MAC-T inflammatory response. bta-miR-199a-3p was up-regulated in the LPS-induced MAC-T cells, while CD2-associated protein (CD2AP) was revealed as its target gene in a double luciferase reporter gene experiment. In addition, the overexpression of bta-miR-199a-3p negatively regulated the expression of CD2AP and the activation of the phosphatidylinositol 3-kinase (PI3K)/AKT/nuclear factor kappa-B (NF-κB) signaling pathway. These subsequently inhibited the secretion of related inflammatory factors (TNF-α, IL-1ß, and IL-6) and the expression of apoptotic genes (CASP3 and CASP9), thereby alleviating the LPS-challenged inflammatory response in the MAC-T cells. Silencing of bta-miR-199a-3p, however, reversed the above effects. Thus, bta-miR-199a-3p inhibits LPS-induced inflammation in bMECs by directly targeting CD2AP and regulating the PI3K/AKT/NF-κB signaling pathway. This study reveals the potential regulatory mechanism of bta-miR-199a-3p in bMEC inflammatory immune response and may serve as a useful target for the treatment of mastitis.