Effect of trace element mixtures on the outcome of patients with esophageal squamous cell carcinoma: a prospective cohort study in Fujian, China.

BACKGROUND: The evidence about the effects of trace elements on overall survival(OS) of patients with esophageal squamous cell carcinoma(ESCC) is limited. This study aims to evaluate mixed effects of plasma trace elements on OS of ESCC. METHODS: This prospective cohort analysis included 497 ESCC patients with a median follow-up of 52.3 months. The concentrations of 17 trace elements were measured. We fitted Cox's proportional hazards regression, factor analysis and Bayesian kernel machine regression (BKMR) models to estimate the association between trace elements and OS. RESULTS: Our analysis found that in the single-element model, Co, Ni, and Cd were associated with an increased risk of death, while Ga, Rb, and Ba were associated with a decreased risk. Cd had the strongest risk effect among all elements. As many elements were found to be mutually correlated, we conducted a factor analysis to identify common factors and investigate their associations with survival time. The factor analysis indicated that the factor with high factor loadings in Ga, Ba and B was linked to a decreased risk of death, while the factor with high factor loadings in Co, Ti, Cd and Pb was associated with a borderline significantly increased risk. Using BKMR analysis to disentangle the interaction between elements in significant factors, we discovered that Ga interacted with Ba and both elements had U-shaped effects with OS. Cd, on the other hand, had no interaction with other elements and independently increased the risk of death. CONCLUSIONS: Our analysis revealed that Ga, Ba and Cd were associated with ESCC outcome, with Ga and Ba demonstrating an interaction. These findings provide new insights into the impact of trace elements on the survival of patients with ESCC.

Extraction of local structure differences in silica based on unsupervised learning.

Silica exhibits a rich phase diagram with numerous stable structures existing at different temperature and pressure conditions, including its glassy form. In large-scale atomistic simulations, due to the small energy difference, several phases may coexist. While, in terms of long-range order, there are clear differences between these phases, their short- or medium-range structural properties are similar for many phases, thus making it difficult to detect the structural differences. In this study, a methodology based on unsupervised learning is proposed to detect the differences in local structures between eight phases of silica, using atomic models prepared by molecular dynamics (MD) simulations. A combination of two-step locality preserving projections (TS-LPP) and locally averaged atomic fingerprints (LAAF) descriptor was employed to find a low-dimensional space in which the differences among all the phases can be detected. From the distance between each structure in the found low-dimensional space, the similarity between the structures can be discussed and subtle local changes in the structures can be detected. Using the obtained low-dimensional space, the ß-α transition in quartz at a low temperature was analyzed, as well as the structural evolution during the melt-quench process starting from α-quartz. The proper differentiation and ease of visualization make the present methodology promising for improving the analysis of the structure and properties of glasses, where subtle differences in structure appear due to differences in the temperature and pressure conditions at which they were synthesized.

An Adaptive Multi-D-Norm-Driven Sparse Unfolding Deconvolutional Network for Bearing Fault Diagnosis.

Impulsive blind deconvolution (IBD) is a popular method to recover impulsive sources for bearing fault diagnosis. Its underpinnings are in the design of objective functions based on prior knowledge of impulsive sources and a transfer function to describe transmission path influences. However, popular objective functions cannot retain waveform impulsiveness and periodicity cyclostationarity simultaneously, and the single convolution operation of IBD methods is insufficient to describe transmission paths composed of multiple linear and nonlinear units. Inspired by the MaxPooling period modulation intensity (MPMI) and convolutional sparse learning (CSL), an adaptive multi-D-norm-driven sparse unfolding deconvolution network (AMD-SUDN) is proposed in this paper. The core strategy is that one target vector with simultaneous impulsiveness and cyclostationarity is constructed automatically through the MPMI; then, this vector is substituted into the multi D-norm to design objective functions. Moreover, an iterative soft threshold algorithm (ISTA) for the CSL model is derived, and its iterative steps are unfolded into one deconvolution network. The algorithm's performance and the hyperparameter configuration are investigated by a set of numerical simulations. Finally, the proposed AMD-SUDN is applied to detect the impulsive features of bearing faults. All comparative results verify that the proposed AMD-SUDN achieves a better deconvolution accuracy than state-of-the-art IBD methods.

Lung-specific exosomes for doxorubicin delivery in lung adenocarcinoma therapy.

Doxorubicin (DOX) could be utilized to treat lung adenocarcinoma (LUAD), while dose-limiting cardiotoxicity limits its clinical utilization. MDA-MB-231 cell-derived exosomes show lung-specific organotropism features. In this study, we aimed to explore the potential of MDA-MB-231 cell-derived exosomes in DOX specific delivery to the lung. MDA-MB-231 cell-derived exosomes were coincubated with to construct for the doxorubicin delivery system (D-EXO). Exosomes labeled with fluorescein isothiocyanate were incubated with A549 cells or 293T cells, and the engulf and the mean intensity of the fluorescence were detected with immunofluorescence and flow cytometry assay. Cell viability was detected with cell counting kit-8 (CCK-8), and cell migration was determined by scratch test. The protein expression was detected by Western blot assay. A549 cell line-derived xenograft mouse model was constructed to examine the treatment effect of D-EXO. MDA-MB-231 cell-derived exosomes could be specially taken up by A549 cells with diminished cell viability but not engulfed by 293T cells. D-EXO inhibited A549 cell migration, and upregulated the protein expression of caspase 3 and cleaved caspase 3 expression, while did not show any inhibition on 293T cells. In vivo orthotopic xenotransplantation model indicated that D-EXO inhibited tumor growth characterized by diminished tumor weight and improved survival rate. No significant change in body weight was observed after the D-EXO treatment. In conclusion, D-EXO proposed in this study could be utilized to treat LUAD with lung-specific delivery effects to improve the survival rate.

Compositional effects on structural, electronic, elastic, piezoelectric and dielectric properties of GaInN alloys: a first-principles study.

We conduct a comprehensive theoretical analysis of wurtzite GaxIn1-xN ternary alloys, focusing on their structural, electronic, elastic, piezoelectric, and dielectric properties through rigorous first-principles calculations. Our investigation systematically explores the influence of varying Ga composition (x = 0%, 25%, 50%, 75%, 100%) on the alloy properties. Remarkably, we observe a distinctive non-linear correlation between the band gap and Ga concentration, attributable to unique slopes in the absolute positions of the valence band maximum and conduction band minimum with respect to Ga concentration. Our effective band structure analysis reveals the meticulous preservation of Bloch characters near band extrema, minimizing charge carrier scattering. Furthermore, we scrutinize deviations from linear Vegard-like dependence in elastic, piezoelectric, and dielectric constants. Additionally, our calculations encompass various optical properties, including absorption coefficient, reflectivity, refractive index, energy loss function, and extinction coefficient. We analyze their trends with photon energy, providing valuable insights into the optical behavior of GaxIn1-xN alloys. Our results, in excellent agreement with available experimental data, significantly contribute to a deeper understanding of the alloys' electronic properties. This study offers valuable insights that may illuminate potential applications of GaxIn1-xN alloys in diverse technological fields.