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Abstract Intestinal-type gastric adenocarcinoma (IGA) is a common phenotype of gastric cancer. Currently, few studies have constructed nomograms that may predict overall (OS) and cancer-specific survival (CSS) probability after surgery. This study is to establish novel nomograms for predicting the survival of IGA patients who received surgery. A total of 1814 IGA patients who received surgery between 2000 and 2018 were selected from Surveillance, Epidemiology, and End Results database and randomly assigned to the training and validating sets at a ratio of 7:3. Then univariate and multivariate cox regression analyses were performed to screen significant indictors for the construction of nomograms. The calibration curve, the area under the receiver operating characteristic (receiver operating characteristic, ROC) curve (the area under curve, AUC), C-index, net reclassification index (NRI), integrated discrimination improvement (IDI) and decision curve analysis (DCA) curves were applied to assess the performance of the model. The significant outcomes of multivariate analysis revealed that ten variables (age, sex, race, surgery type, summary stage, grade, AJCC TNM stage, radiotherapy, number of regional nodes examined, number of regional nodes positive) were demonstrated to construct the nomogram for OS and ten variables (age, sex, race, surgery type, summary stage, grade, AJCC TNM stage, chemotherapy, number of regional nodes examined, number of regional nodes positive) for CSS. The calibration and AUC uncovered their favorable predictive performance. Subsequently, C-index, NRI, IDI and DCA curves further validated the predicative superiority of nomograms over 7th AJCC Stage System. The validated nomogram provides more reliable OS and CSS predictions for postoperative IGA patients with good accuracy, which can help surgeons in treatment decision-making and prognosis evaluation.

Abstract The pathological features of Alzheimer's disease are the formation of amyloid plaques and entanglement of nerve fibers. Studies have shown that Cu may be involved in the formation of amyloid plaques. However, their role has been controversial. The aim of this study was to explore the role of Cu in AD. We applied the “R” software for our differential analysis. Differentially expressed genes were screened using the limma package. Copper metabolism-related genes and the intersection set of differential genes with GSE5281 were searched; functional annotation was performed. The protein–protein interaction network was constructed using several modules to analyse the most significant hub genes. The hub genes were then qualified, and a database was used to screen for small-molecule AD drugs. We identified 87 DEGs. gene ontology analysis focused on homeostatic processes, response to toxic substances, positive regulation of transport, and secretion. The enriched molecular functions are mainly related to copper ion binding, molecular function regulators, protein-containing complex binding, identical protein binding and signalling receptor binding. The KEGG database is mainly involved in central carbon metabolism in various cancers, Parkinson's disease and melanoma. We identified five hub genes, FGF2, B2M, PTPRC, CD44 and SPP1, and identified the corresponding small molecule drugs. Our study identified key genes possibly related to energy metabolism in the pathological mechanism of AD and explored potential targets for AD treatment by establishing interaction networks.

Abstract In this paper, we propose a new type of nonlinear strict distance and similarity measures for intuitionistic fuzzy sets (IFSs). Our proposed methods not only have good properties, but also improve the drawbacks proposed by Mahanta and Panda (Int J Intell Syst 36(2):615–627, 2021) in which, for example, their distance value of $$d_{_{\textrm{MP}}}(\langle \mu , \nu \rangle , \langle 0, 0\rangle )$$ d MP ( ⟨ μ , ν ⟩ , ⟨ 0 , 0 ⟩ ) is always equal to the maximum value 1 for any intuitionistic fuzzy number $$\langle \mu , \nu \rangle \ne \langle 0, 0\rangle $$ ⟨ μ , ν ⟩ ≠ ⟨ 0 , 0 ⟩ . To resolve these problems in Mahanta and Panda (Int J Intell Syst 36(2):615–627, 2021), we establish a nonlinear parametric distance measure for IFSs and prove that it satisfies the axiomatic definition of strict intuitionistic fuzzy distances and preserves all advantages of distance measures. In particular, our proposed distance measure can effectively distinguish different IFSs with high hesitancy. Meanwhile, we obtain that the dual similarity measure and the induced entropy of our proposed distance measure satisfy the axiomatic definitions of strict intuitionistic fuzzy similarity measure and intuitionistic fuzzy entropy. Finally, we apply our proposed distance and similarity measures to pattern classification, decision making on the choice of a proper antivirus face mask for COVID-19, and medical diagnosis problems, to illustrate the effectiveness of the new methods.

Abstract Materials properties depend not only on their compositions but also their microstructures under various processing conditions. So far, the analyses of complex microstructure images rely mostly on human experience, lack of automatic quantitative characterization methods. Machine learning provides an emerging vital tool to identify various complex materials phases in an intelligent manner. In this work, we propose a “center-environment segmentation” (CES) feature model for image segmentation based on machine learning method with environment features and the annotation input of domain knowledge. The CES model introduces the information of neighbourhood as the features of a given pixel, reflecting the relationships between the studied pixel and its surrounding environment. Then, an iterative integrated machine learning method is adopted to train and correct the image segmentation model. The CES model was successfully applied to segment seven different material images with complex texture ranging from steels to woods. The overall performance of the CES method in determining boundary contours is better than many conventional methods in the case study of the segmentation of steel image. This work shows that the iterative introduction of domain knowledge and environment features improve the accuracy of machine learning based image segmentation for various complex materials microstructures.

The process of photocatalysis is appealing to huge interest motivated by the great promise of addressing current energy and environmental issues through converting solar light directly into chemical energy. However, an efficient solar energy harvesting for photocatalysis remains a critical challenge. Here, we reported a new full solar spectrum driven photocatalyst by co-doping of Gd3+ and Sn4+ into A and B-sites of BiFeO3 simultaneously. The co-doping of Gd3+ and Sn4+ played a key role in hampering the recombination of electron-hole pairs and shifted the band-gap of BiFeO3 from 2.10 eV to 2.03 eV. The Brunauer-Emmett-Teller (BET) measurement confirmed that the co-doping of Gd3+ and Sn4+ into BiFeO3 increased the surface area and porosity, and thus the photocatalytic activity of the Bi0.90Gd0.10Fe0.95Sn0.05O3 system was significantly improved. Our work proposed a new photocatalyst that could degrade various organic dyes like Congo red, Methylene blue, and Methyl violet under irradiation with different light wavelengths and gave guidance for designing more efficient photocatalysts. [ABSTRACT FROM AUTHOR]

Contrast enhancement (CE) on brain non-contrast computed tomography (NCCT) is common after endovascular thrombectomy (EVT) in patients with acute ischemic stroke (AIS), but its association with clinical outcomes is not well established. The current study aimed to investigate this relationship. We retrospectively reviewed consecutive patients with acute ischemic stroke who had hyperdensity on NCCT immediately after EVT for anterior circulation large vessel occlusion (LVO) from January 2016 to December 2019. We used ASPECTS combined with volume measurement by 3D reconstruction to estimate the extent and location of CE. Multivariable regression analysis was conducted to explore the risk factors associated with clinical outcome. In this study, 113 of 158 (71.52%) anterior circulation AIS-LVO patients had hyperdensity on brain NCCT. After strict inclusion and exclusion criteria, a total of 64 patients were enrolled in the final analysis. In logistic regression analysis, CE-ASPECTS, CE volume, CE at the caudate nucleus, M4 and M6 region were associated with 3-month poor functional outcome after adjusting for confounding factors. The conventional variable model was used for reference, including age, initial NIHSS, the procedure time, stent retriever passes, recanalization status and baseline ASPECTS, with AUC of 0.73. When combined with the above-named variables (conventional variables + CE-ASPECTS + CE volume + CE at caudate nucleus + CE at M4 region + CE at M6 region), the predictive power was significantly improved, with AUC of 0.87 (95% CI 0.78-0.95). The spatial location and volume of CE on NCCT obtained immediately after EVT were independent and strong predictors for poor outcome at 3-months in patients with AIS after excluding definite hemorrhage by 24-h follow up CT., (© 2022. The Author(s).)

Rheumatoid arthritis (RA) is a chronic inflammatory disease characterized by proliferation and insufficient apoptosis of fibroblast-like synoviocytes (FLSs).The biology and functions of interleukin (IL)-34 are only beginning to be uncovered. We previously demonstrated IL-34 could upregulate the expression of IL-17 in RA patients. In this study, the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and flow cytometry of Annexin V and PI staining were performed to assess cell proliferation and apoptosis progression in RA-FLSs after stimulated with increasing concentrations of IL-34, respectively. Inflammatory cytokines and angiogenic factors were measured using quantitative real-time PCR, Western blotting and ELISA. We explored the association between IL-34 and RA-FLS proliferation and apoptosis in the context of RA. Stimulating RA-FLSs with different concentrations of IL-34 significantly promoted the proliferation and inhibited the apoptosis of RA-FLSs in a concentration-dependent manner. Neutralization of IL-17 with the IL-17 inhibitor plumbagin (PB) reduced the effects of IL-34. Proinflammatory cytokine (IL-17A IL-6 and tumor necrosis factor-α, TNF-α) and angiogenic factor (vascular endothelial growth factor, VEGF and hypoxia-inducible factor-1α, HIF-1α) expression was markedly upregulated in RA-FLSs stimulated by IL-34. PB-mediated inhibition of IL-17A also decreased the expression of IL-6, TNF-α, HIF-1α and VEGF in RA-FLSs. Taken together, these findings suggest that targeting IL-34 production in RA-FLSs may be a therapeutic strategy for RA., (© 2021. The Author(s).)

To determine whether the traditional Chinese medicine Tongxinluo (TXL) is efficacious at retarding the progression of carotid atherosclerotic lesions, a total of 1,212 patients with a focal intima-media thickness (IMT) of ≥1.2 mm of the carotid arteries received TXL or placebo capsules in addition to current routine therapy. The primary outcome was between-group differences in annualized change in mean IMT of 12 sites of bilateral carotid arteries over 24 months. The secondary outcomes were between-group differences in plaque area, vascular remodeling index (RI), serum levels of lipids and high-sensitivity C-reactive protein, and a composite of first major cardiovascular events. The results showed that the annualized change in mean IMT in the TXL and placebo groups was -0.00095 (95% CI, -0.00330 to 0.00141) mm and 0.01312 (95% CI, 0.01076 to 0.01548) mm, respectively, with a difference between the two groups of -0.01407 (95% CI, -0.01740 to -0.01073) mm (P < 0.001). Compared with placebo, TXL treatment significantly reduced the change from baseline in the plaque area and RI, as well as the first major cardiovascular events. In conclusion, TXL retarded the progression of mean IMT, plaque area and vascular remodeling of the carotid artery with a good safety profile.

The present study is to establish a nomogram for predicting the prognosis of IgA nephropathy (IgAN). Of the 869 IgAN patients, four-fifths were randomly assigned to the development cohort and one-fifth to the validation cohort. The primary outcome was a composite event of either a ≥ 50% reduction in estimated glomerular filtration rate (eGFR), end-stage renal disease or death. The mean follow-up time was 44 months. The Cox regression model identified urinary protein excretion (1-3.5 g/d, HR 11.639, 95% CI 3.601-37.625; ≥ 3.5 g/d, HR 32.435, 95% CI 10.079-104.380), eGFR (G2, HR 5.293, 95% CI 2.011-13.932; G3, HR 15.797, 95% CI 6.584-37.905; G4, HR 34.619, 95% CI 13.887-86.301; G5, HR 217.651, 95% CI 83.807-565.248), hyperuricaemia (HR 7.031, 95% CI 4.126-11.980), mesangial proliferation (HR 36.667, 95% CI 5.098-263.711), segmental glomerulosclerosis (HR 5.122, 95% CI 3.114-8.425), tubular atrophy/interstitial fibrosis (T1, HR 33.351, 95% CI 7.831-142.044; T2, HR 213.888, 95% CI 51.048-896.182), crescents (C1, HR 3.123, 95% CI 1.771-5.510; C2, HR 7.353, 95% CI 3.590-15.062) and glomerulosclerosis (25-49%, HR 3.123, 95% CI 1.771-5.510; ≥ 50%, HR 14.384, 95% CI 8.813-23.479) for developing the nomogram. The C-index was 0.945 (95% CI 0.914-0.976) in both the development and validation cohorts, showing good agreement between the nomogram-predicted probability and actual free-of-progression probability. Thus, our nomogram could accurately predict the progression of IgAN patients.

We measured the interleukin-34 (IL-34) level in sera from patients with systemic lupus erythematosus (SLE) and discoid lupus erythematosus (DLE) using an enzyme-linked immunosorbent assay (ELISA). Blood tests, including assays to determine C-reactive protein (CRP), complement (C) 3, C4, immunoglobulin (Ig) A, IgG, IgM, anti-double-stranded DNA antibody (Anti-dsDNA Ab) and hemoglobin (Hb) levels and white blood cell (WBC) and platelet (PLT) counts, were performed using standard methods. Lupus nephritis (LN) was diagnosed according to the American College of Rheumatology (ACR) renal criteria. The SLE disease activity was scored using the SLE Disease Activity Index (SLEDAI). Among the 110 SLE cases, IL-34 could be detected in 79 cases (71.8%). IL-34 was barely detected in the control group. The serum level of IL-34 was significantly higher in the SLE group. No change was observed in the serum IL-34 concentration in the SLE patients regardless of LN status. Correlations were observed between the serum IL-34 level and the disease activity parameters. The SLE patients with detectable IL-34 levels had higher SLEDAI and IgG concentrations and lower C3 and Hb levels than patients with undetectable IL-34 levels. Therefore, IL-34 could be a potential disease activity marker for SLE.

Various forms of oncogenic ALK proteins have been identified in various types of human cancers. While Crizotinib, an ALK inhibitor, has been found to be therapeutically useful against a subset of ALK(+) tumours, clinical resistance to this drug has been well recognized and the mechanism of this phenomenon is incompletely understood. Using the cellular thermal shift assay (CETSA), we measured the Crizotinib-ALK binding in a panel of ALK(+) cell lines, and correlated the findings with the ALK structure and its interactions with specific binding proteins. The Crizotinib IC50 significantly correlated with Crizotinib-ALK binding. The suboptimal Crizotinib-ALK binding in Crizotinib-resistant cells is not due to the cell-specific environment, since transfection of NPM-ALK into these cells revealed substantial Crizotinib-NPM-ALK binding. Interestingly, we found that the resistant cells expressed higher protein level of β-catenin and siRNA knockdown restored Crizotinib-ALK binding (correlated with a significant lowering of IC50). Computational analysis of the crystal structures suggests that β-catenin exerts steric hindrance to the Crizotinib-ALK binding. In conclusion, the Crizotinib-ALK binding measurable by CETSA is useful in predicting Crizotinib sensitivity, and Crizotinib-ALK binding is in turn dictated by the structure of ALK and some of its binding partners.

Cataracts are the leading cause of vision loss in the world, although surgical treatment can restore vision in cataract patients. Until now, there have been no adequate animal models for in vivo studies of artificial lens safety and drug interactions. Genetic studies have demonstrated that GJA8 is involved in maintaining lens opacity and proper lens development. In this study, a cataract model with GJA8 gene knockout was developed via co-injection of Cas9/sgRNA mRNA into rabbit zygotes. Our results showed that gene mutation efficiency in the GJA8 locus reached 98.7% in embryos and 100% in pups, demonstrating that the Cas9/sgRNA system is a highly efficient tool for gene editing in rabbits. In agreement with other studies, our genetic and histology results showed that impaired GJA8 function caused microphthalmia, small lens size and cataracts. In summary, our novel rabbit model of cataracts will be an important drug-screening tool for cataract prevention and treatment.