Interpretable domain knowledge enhanced machine learning framework on axial capacity prediction of circular CFST columns

This study introduces a novel machine learning framework, integrating domain knowledge, to accurately predict the bearing capacity of CFSTs, bridging the gap between traditional engineering and machine learning techniques. Utilizing a comprehensive database of 2621 experimental data points on CFSTs, we developed a Domain Knowledge Enhanced Neural Network (DKNN) model. This model incorporates advanced feature engineering techniques, including Pearson correlation, XGBoost, and Random tree algorithms. The DKNN model demonstrated a marked improvement in prediction accuracy, with a Mean Absolute Percentage Error (MAPE) reduction of over 50% compared to existing models. Its robustness was confirmed through extensive performance assessments, maintaining high accuracy even in noisy environments. Furthermore, sensitivity and SHAP analysis were conducted to assess the contribution of each effective parameter to axial load capacity and propose design recommendations for the diameter of cross-section, material strength range and material combination. This research advances CFST predictive modelling, showcasing the potential of integrating machine learning with domain expertise in structural engineering. The DKNN model sets a new benchmark for accuracy and reliability in the field.Comment: Journal Research Articl

Food Safety Regulatory System of Developed Countries and the Implication for China

The problem of food safety has become a focus in the world. In recent years, because of high frequency of food safety accidents, the problems of food safety have appealed much concern in China. This article introduces the features of the food safety regulation of the developed countries and then offers suggestions and the successful experiences that we should learn from when China is establishing our own food safety regulatory system. Key words: food safety; regulatory system; regulatory mod

GFI1 downregulation promotes inflammation-linked metastasis of colorectal cancer.

Inflammation is frequently associated with initiation, progression, and metastasis of colorectal cancer (CRC). Here, we unveil a CRC-specific metastatic programme that is triggered via the transcriptional repressor, GFI1. Using data from a large cohort of clinical samples including inflammatory bowel disease and CRC, and a cellular model of CRC progression mediated by cross-talk between the cancer cell and the inflammatory microenvironment, we identified GFI1 as a gating regulator responsible for a constitutively activated signalling circuit that renders CRC cells competent for metastatic spread. Further analysis of mouse models with metastatic CRC and human clinical specimens reinforced the influence of GFI1 downregulation in promoting CRC metastatic spread. The novel role of GFI1 is uncovered for the first time in a human solid tumour such as CRC. Our results imply that GFI1 is a potential therapeutic target for interfering with inflammation-induced CRC progression and spread

Mutations associated with no durable clinical benefit to immune checkpoint blockade in Non-S-Cell lung cancer

(1) Background: The immune checkpoint blockade (ICB) has shown promising efficacy in non-small-cell lung cancer (NSCLC) patients with significant clinical benefits and durable responses, but the overall response rate to ICBs is only 20%. The lack of responsiveness to ICBs is currently a central problem in cancer immunotherapy. (2) Methods: Four public cohorts comprising 2986 patients with NSCLC were included in the study. We screened 158 patients with NSCLC with no durable clinical benefit (NDB) to ICBs in the Rizvi cohort and identified NDB-related gene mutations in these patients using univariate and multivariate Cox regression analyses. Programmed death-ligand 1 (PD-L1) expression, tumor mutation burden (TMB), neoantigen load, tumor-infiltrating lymphocytes, and immune-related gene expression were analyzed for identifying gene mutations. A comprehensive predictive classifier model was also built to evaluate the efficacy of ICB therapy. (3) Results: Mutations in FAT1 and KEAP1 were found to correlate with NDB in patients with NSCLC to ICBs; however, the analysis suggested that only mutation in FAT1 was valuable in predicting the efficacy of ICB therapy, and that mutation in KEAP1 acted as a prognostic but not a predictive biomarker for NSCLC. Mutations in FAT1 were associated with a higher TMB and lower multiple lymphocyte infiltration, including CD8 (T-Cell Surface Glycoprotein CD8)+ T cells. We established a prognostic model according to PD-L1 expression, TMB, smoking status, treatment regimen, treatment type, and FAT1 mutation, which indicated good accuracy by receiver operating characteristic (ROC) analysis (area under the curve (AUC) for 6-months survival: 0.763; AUC for 12-months survival: 0.871). (4) Conclusions: Mutation in FAT1 may be a predictive biomarker in patients with NSCLC who exhibit NDB to ICBs. We proposed an FAT1 mutation-based model for screening more suitable NSCLC patients to receive ICBs that may contribute to individualized immunotherapy.info:eu-repo/semantics/publishedVersio

Analysis of Epithelial Growth Factor-Receptor (EGFR) Phosphorylation in Uterine Smooth Muscle Tumors

Uterine fibroids are the commonest uterine benign tumors. A potential mechanism of malignant transformation from leiomyomas to leiomyosarcomas has beendescribed. Tyrosine phosphorylation is a key mechanism that controls biological functions, such as proliferation and cell differentiation. The aim of the current study was to evaluate the phosphorylation of epithelial growth factor-receptor (EGFR) in normal myometrium, uterine myomas and uterine leiomyosarcomas. Formalin-fixed paraffin-embedded tissue samples from normal myometrium, leiomyomas and leiomyosarcomas were studied. Samples were immunohistochemically (IHC) assessed using the anti-EGFR phosphorylation of Y845 (pEGFR-Y845) and anti-pEGFR-Y1173 phosphorylation-specific antibodies. IHC staining was evaluated using a semiquantitative score. The expression of pEGFR-Y845 was significantly upregulated in leiomyosarcomas (p < 0.001) compared to leiomyomas and normal myometrium. In contrast, pEGFR-Y1173 did not differ significantly between the three groups of the study. Correlation analysis revealed an overall positive correlation between pEGFR Y845 and mucin 1 (MUC1). Further subgroup analysis within the tumoral group (myomas and leiomyosarcomas) revealed an additional negative correlation between pEGFR Y845 and galectin-3 (gal-3) staining. On the contrary no significant correlation was noted within the non-tumoral group. An upregulated EGFR phosphorylation of Y845 in leiomyosarcomas compared to leiomyomas implicates EGFR activation at this special receptor site. Due to these pEGFR-Y845 variations, it can be postulated that MUC1 interacts with it, whereas gal-3 seems to be cleaved from Y845 phosphorylated EGFR. Further research on this field could focus on differences in EGFR pathways as a potentially advantageous diagnostic tool for investigation of benign and malignant signal transduction processes

Trypsin-ligand binding free energies from explicit and implicit solvent simulations with polarizable potential

We have calculated the binding free energies of a series of benzamidine-like inhibitors to trypsin with a polarizable force field using both explicit and implicit solvent approaches. Free energy perturbation has been performed for the ligands in bulk water and in protein complex with molecular dynamics simulations. The calculated binding free energies are well within the accuracy of experimental measurement and the direction of change is predicted correctly in call cases. We analyzed the molecular dipole moments of the ligands in gas, water and protein environments. Neither binding affinity nor ligand solvation free energy in bulk water shows much dependence on the molecular dipole moments of the ligands. Substitution of the aromatic or the charged group in the ligand results in considerable change in the solvation energy in bulk water and protein whereas the binding affinity varies insignificantly due to cancellation. The effect of chemical modification on ligand charge distribution is mostly local. Replacing benzene with diazine has minimal impact on the atomic multipoles at the amidinium group. We have also utilized an implicit solvent based end-state approach to evaluate the binding free energies of these inhibitors. In this approach, the polarizable multipole model combined with Poisson-Boltzmann/surface area (PMPB/SA) provides the electrostatic interaction energy and the polar solvation free energy. Overall the relative binding free energies obtained from the PMPB/SA model are in good agreement with the experimental data