Developing a hybrid technique for energy demand forecasting based on optimized improved SVM by the boosted multi-verse optimizer: Investigation on affecting factors.

Electricity demand prediction accuracy is crucial for operational energy resource management and strategy. In this study, we provide a multi-form model for electricity demand prediction in China that based on incorporating of an upgraded Support Vector Machine (SVM) and a Boosted Multi-Verse Optimizer (BMVO). The suggested model is proposed to address the shortcomings of existing prediction approaches, which frequently fail to internment the complicated nonlinear interactions between demand for electricity and the variables that influence it. The improved SVM algorithm incorporates a modified genetic algorithm based on kernel function for enhancing the stability of the model. The BMVO technique is employed to optimize the combined model's weights and increase its generalization effectiveness. The suggested approach is tested by real-world Chinese energy demand data. The findings show that it outperforms existing prediction approaches in terms of reliability and precision. Further, the number of samples chosen affects how well the proposed BMVO linked with the Incremental SVM (ISVM) predicts outcomes. Particularly, when 1735 samples are chosen, the lowest level of Mean Absolute Percent Error (MAPE) was noted. The Root Mean Square Error (RMSE) and MAPE values under the proposed BMVO/ISVM model are reduced by 53.72% and 55.22%, respectively, compared to the Artificial Neural Network (ANN) approach reported in literature. Finally, the suggested model is capable of accurately predicting the electricity demand in China and has the potential to be applied to other energy-demand prediction applications.

ELAPOR1 suppresses tumor progression in colorectal cancer and indicates favorable prognosis.

BACKGROUND: The role of ELAPOR1 has been evaluated in several cancers but has not been elucidated in colorectal cancer (CRC). OBJECTIVE: To investigate the role of ELAPOR1 in CRC. METHODS: In the present study, the correlation between ELAPOR1 and survival of CRC patients in TCGA-COAD-READ datasets was predicted, and the difference in ELAPOR1 expression between tumor and normal tissues was analyzed. ELAPOR1 expression in CRC tissues was measured by immunohistochemistry. Then, ELAPOR1 and ELAPOR1-shRNA plasmids were constructed and transfected into SW620 and RKO cells. The effects were assessed by CCK-8, colony formation, transwell, and wound healing assays. Transcriptome sequencing and bioinformatics analysis were performed on the genes before and after ELAPOR1 overexpression in SW620 cells; the differentially expressed genes were substantiated by real-time quantitative reverse transcription PCR. RESULTS: High level of ELAPOR1 is associated with favorable disease-free survival and overall survival. Compared to normal mucosa, ELAPOR1 is lower in CRC. Moreover, ELAPOR1 overexpression significantly inhibits cell proliferation and invasion in vitro in SW260 and RKO cells. Conversely, ELAPOR1-shRNA promotes CRC cell proliferation and invasion. Among the 355 differentially expressed mRNAs identified, 234 were upregulated and 121 were downregulated. Bioinformatics indicated that these genes are involved in receptor binding, plasma membrane, negative regulation of cell proliferation, as well as common cancer signaling pathways. CONCLUSIONS: ELAPOR1 plays an inhibitory role in CRC and may be used as a prognostic indicator and a potential target for treatment.

Data-Independent Acquisition-Based Mass Spectrometry (DIA-MS) for Quantitative Analysis of Human Intestinal Ischemia/Reperfusion.

Intestinal ischemia-reperfusion (II/R) injury is a complex pathologic process, which is of great significance to unravel the underlying mechanisms and pathophysiology. Our study represented a comprehensive proteomic analysis in the human intestine with ischemia-reperfusion injury. The proteomics analysis measured a total of 5,230 proteins, and 417 differently expressed proteins (DEPs) were identified between II/R and control samples. GO and KEGG analysis demonstrated that the 290 upregulated DEPs in II/R were significantly involved in immune-related biological process and tight junction, focal adhesion, and cAMP signaling pathway, whereas the 127 downregulated DEPs in II/R were enriched in lipid metabolic process and metabolic pathway. Furthermore, we screened out 20 hub proteins from the protein-protein interaction (PPI) network according to the degree of connectivity, and six clusters were identified. Combined with the result of KEGG analysis, 6 from the 20 hub proteins, ACTB, CAV1, FLNA, MYLK, ACTN1, and MYL9, were identified as the key proteins in the progress of II/R injury. According to the previous studies, FLNA and MYL9 were selected as the novel disease-related proteins for the first time. In conclusion, this study extended our understanding of the alteration in the human intestine during ischemia and reperfusion and highlighted the potential role of FLNA and MYL9 in the progress of II/R injury, which need to be further studied.

Molecular design and validation of halogen bonding orthogonal to hydrogen bonding in breast cancer MDM2-peptide complex.

Peptide therapeutics has been raised as an attractive approach for the treatment of breast cancer by targeting the oncogenic protein MDM2 that inactivates p53 tumor suppressor. Here, we performed molecular design of halogen bonding orthogonal to hydrogen bonding at the complex interface of MDM2 protein with its cognate peptide ligand to improve the peptide binding affinity and specificity. Crystal structure analysis, high-level quantum chemistry (QC) calculations and combined quantum mechanics/molecular mechanics (QM/MM) modeling revealed that halogen substitution at position 3 of the benzene moiety of peptide Phe3 residue can constitute a putative halogen bonding, which is shown to be geometrically perpendicular to and energetically independent of a native hydrogen bonding that share a common carbonyl oxygen acceptor. The designed halogen bonding was then validated by surface plasmon resonance (SPR) assays, that is, substitution with bromine at position 3 can considerably improve peptide affinity by ∼4-fold, but the peptide binding does not change substantially upon the bromine substitution at other positions of the Phe3 benzene moiety (the negative controls that are theoretically unable to form the halogen bonding), indicating that the orthogonal molecular interaction (OMI) system between the designed halogen bonding and native hydrogen bonding can co-work well at the complex interface of MDM2 protein with its halogenated peptide ligands.

Genetic variability of glutathione S-transferases influences treatment outcome of breast cancer.

We investigated the relationship between the clinical outcome and the GSTM1 null/present, GSTT1 null/present, and GSTP1 IIe105Val polymorphisms in breast cancer patients with chemotherapy. A total of 420 consecutive breast cancer patients diagnosed between January 2010 and December 2011 were eligible for inclusion in our retrospective study. The designs of the assay and SNP genotyping of GSTM1 null/present, GSTT1 null/present, and GSTP1 IIe105Val were performed using the Sequenom MassARRAY platform. In the univariate analysis, patients who carried TT genotype and CT + TT genotype of GSTP1 IIe105Val showed a significant poorer tumor response to chemotherapy when compared with CC genotype (for TT genotype, adjusted OR = 0.44, 95 % CI = 0.22-0.89; for CT + TT genotype, adjusted OR = 0.59, 95 % CI = 0.39-0.92). By Cox multivariate analysis, TT genotype and CT + TT genotype were associated with increased risk of death from breast cancer, and the relationship was more obvious after being adjusted by potential confounding factors (for TT genotype, adjusted OR = 4.23, 95 % CI = 2.33-8.76; for CT + TT genotype, adjusted OR = 2.53, 95% CI = 1.60-4.03). Polymorphism of GSTP1 IIe105Val might affect the clinical outcome in breast cancer patients.