TOMM40 Correlates with Cholesterol and is Predictive of a Favorable Prognosis in Endometrial Carcinoma.

BACKGROUND: A link between cholesterol and endometrial cancer has been established, but current studies have been limited in their findings. We aimed to elucidate the causal relationship between cholesterol and endometrial cancer and to find prognostic genes for endometrial cancer. METHODS: We first explored the causal relationship between total cholesterol and endometrial cancer using two-sample Mendelian randomization and then obtained differential genes to screen for prognosis-related genes in endometrial cancer. Then, we utilized pan-cancer analysis based on RNA sequencing data to evaluate the expression pattern and immunological role of the Translocase of Outer Mitochondrial Membrane 40 (TOMM40). Through multiple transcriptome datasets and multi-omics in-depth analysis, we comprehensively explore the relationship of TOMM40 expression with clinicopathologic characteristics, clinical outcomes and mutations in endometrial cancer. Lastly, we systematically associated the TOMM40 with different cancers from immunological properties from numerous perspectives, such as immune cell infiltration, immune checkpoint inhibitors, immunotherapy, gene mutation load and microsatellite instability. RESULTS: We found a negative association between cholesterol and endometrial cancer. A total of 78 genes were enriched by relevant single nucleotide polymorphisms (SNPs), of which 12 upregulated genes and 5 downregulated genes in endometrial cancer. TOMM40 was found to be a prognostic gene associated with endometrial cancer by prognostic analysis. TOMM40 was found to be positively correlated with the infiltration of most immune cells and immunization checkpoints in a subsequent study. Meanwhile, TOMM40 also was an oncogene in many cancer types. High TOMM40 was associated with lower genome stability. CONCLUSION: The findings of our study indicate that the maintenance of normal total cholesterol metabolism is associated with a decreased risk of developing endometrial cancer. Moreover, TOMM40 may have potential as a prognostic indicator for endometrial cancer.

Recyclable low-temperature phase change microcapsules for cold storage.

Recyclable low-temperature phase change microcapsules (LTPCMs) have the potential applications in the short-distance cold chain transportation due to their reliable reusability in cold storage. Herein, LTPCMs are synthesized via in-situ suspension copolymerization of styrene and methyl methacrylate in absence of harm substances, providing the non-crosslinking copolymer shells. n-Dodecane, n-tridecane and n-tetradecane, inducing the microphase separation of non-crosslinking copolymers, are successfully encapsulated to achieve n-do-LTPCMs, n-tri-LTPCMs and n-tetra-LTPCMs, which respectively bear the high phase change enthalpy of 110.53 J·g-1 at -8.69 °C, 38.33 J·g-1/93.71 J·g-1 at -17.61 °C/-4.96 °C and 166.79 J·g-1 at 8.59 °C and subsequently show the cold-discharging periods of 30 min, 40 min and 120 min. The multiple circulation of cold-discharging process indicates the excellent recyclability for cold storage owing to their unchanged cold-discharging period. Especially, n-tetra-LTPCM-65 bears the best comprehensive cold-storing performance in all the previously reported LTPCMs, such as narrow cold-discharging temperature range of 3-4 °C, long cold-discharging period of 69-120 min and low cold-discharging capacity of 33.4 J·g-1·K-1. This work successfully provided the recyclable LTPCMs for cold storage in the short-distance cold chain transportation.

L(p) approximation capabilities of sum-of-product and sigma-pi-sigma neural networks.

This paper studies the L(p) approximation capabilities of sum-of-product (SOPNN) and sigma-pi-sigma (SPSNN) neural networks. It is proved that the set of functions that are generated by the SOPNN with its activation function in $L_{loc};p(\mathcal{R})$ is dense in $L;p(\mathcal{K})$ for any compact set $\mathcal{K}\subset \mathcal{R};N$, if and only if the activation function is not a polynomial almost everywhere. It is also shown that if the activation function of the SPSNN is in ${L_{loc};\infty(\mathcal{R})}$, then the functions generated by the SPSNN are dense in $L;p(\mathcal{K})$ if and only if the activation function is not a constant (a.e.).