Background: Globally, gastric cancer (GC) is the fifth most common tumor. It is necessary to identify novel molecular subtypes to guide patient selection for specific target therapeutic benefits. Methods: Multi-omics ...
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Background: Globally, gastric cancer (GC) is the fifth most common tumor. It is necessary to identify novel molecular subtypes to guide patient selection for specific target therapeutic benefits. Methods: Multi-omics data, including transcriptomics RNA-sequencing (mRNA, LncRNA, miRNA), DNA methylation, and gene mutations in the TCGA-STAD cohort were used for the clustering. Ten classical clustering algorithms were executed to recognize patients with different molecular features using the "MOVICS" package in R. The activated signaling pathways were evaluated using the single-sample gene set enrichment analysis. The differential distribution of gene mutations, copy number alterations, and tumor mutation burden was compared, and potential responses to immunotherapy and chemotherapy were also assessed. Results: Two molecular subtypes (CS1 and CS2) were recognized by ten clustering algorithms with consensus ensembles. Patients in the CS1 group had a shorter average overall survival time (28.5 vs. 68.9 months, P = 0.016), and progression-free survival (19.0 vs. 63.9 months, P = 0.008) as compared to those in the CS2 group. Extracellular associated biological process activation was higher in the CS1 group, while the CS2 group displayed the enhanced activation of cell cycle-associated pathways. Significantly higher total mutation numbers and neoantigens were observed in the CS2 group, along with specific mutations in TTN, MUC16, and ARID1A. Higher infiltration of immunocytes was also observed in the CS2 group, reflective of the potential immunotherapeutic benefits. Moreover, the CS2 group could also respond to 5-fluorouracil, cisplatin, and paclitaxel. The similar diversity in clinical outcomes between CS1 and CS2 groups was successfully validated in the external cohorts, GSE62254, GSE26253, GSE15459, and GSE84437. Conclusion: The findings provided novel insights into the GC subtypes through integrative analysis of five -omics data by ten clustering algorithms. These could
Scope: Tropomyosin (TPM), an actin-binding protein widely expressed across different cell types, is primarily involved in cellular contractile processes. We investigated whether TPM3 physically and functionally intera...
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Scope: Tropomyosin (TPM), an actin-binding protein widely expressed across different cell types, is primarily involved in cellular contractile processes. We investigated whether TPM3 physically and functionally interacts with stromal interaction molecule 1 (STIM1) to contribute to vascular smooth muscle cell (VSMC) contraction, store-operated calcium entry (SOCE), and high-salt intake-induced hypertension in rats. Methods and results: Analysis of a rat RNA-seq data set of 80 samples showed that the STIM1 and Tpm3 transcriptome expression pattern is highly correlated, and co-immunoprecipitation results indicated that TPM3 and STIM1 proteins physically interacted in rat VSMCs. Immunohistochemical data displayed obvious co-localization of TPM3 and STIM1 in rat VSMCs. Knockdown of TPM3 or STIM1 in VSMCs with specific small interfering RNA significantly suppressed contractions in tension measurement assays and decreased SOCE in calcium assays. Rats fed a high-salt diet for 4 weeks had significantly higher systolic blood pressure than controls, with significantly increased contractility and markedly increased TPM3 and STIM1 expression levels in the mesenteric resistance artery (shown by tension measurements and immunoblotting, respectively). Additionally, high salt environment in vitro induced significant enhancement of TPM3 and STIM1 expression levels in VSMCs. Conclusions: We showed for the first time that TPM3 and STIM1 physically and functionally interact to contribute to VSMC contraction, SOCE, and high-salt intake-induced hypertension. Our findings provide mechanistic insights and offer a potential therapeutic target for high-salt intake-induced hypertension.
HLEpiCs were cultured with normal glucose (5.5 mM) or high glucose (25.6 mM) for 1, 3, 7, and 14 days and found that compared with the cells in normal glucose, the Ca2+ influx via SOCE was significantly increased in t...
HLEpiCs were cultured with normal glucose (5.5 mM) or high glucose (25.6 mM) for 1, 3, 7, and 14 days and found that compared with the cells in normal glucose, the Ca2+ influx via SOCE was significantly increased in the high glucose group after either thapsigargin (TG) or ATP treatment, and the increase in SOCE was greater when the high glucose treatment lasted longer (Figure 1).
[...]compared with those in the cells in normal glucose, the expression levels of Orai3 and STIM1 proteins were significantly enhanced in the cells in high glucose on each day (Figure S2A, B, and E).
The fasting blood glucose levels were significantly higher both in streptozotocin-injected Orai3–/– and wild-type rats compared to control Orai3–/– and wild-type rats (Figure 2D–G).
[...]the lens turbidity levels were markedly higher both in diabetic Orai3–/– and wild-type rats compared to control Orai3–/– and wild-type rats (Figure 2H–I), but interestingly, the lens turbidity levels were significantly lower in Orai3–/– diabetic rats compared with wild-type diabetic rats (Figure 2H–I).
[...]the results in animal models strongly suggest that Orai3 may be importantly involved in the development of DC.
In our study, we provided evidence that a high glucose environment increased the apoptotic ratio of the lens epithelial cells, which would contribute to lens opacities.
This paper considers the finite-time tracking control problem for the strict-feedback nonlinear continuous systems involving input saturation and output constraints. A sequence of desired and auxiliary virtual control...
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This paper considers the finite-time tracking control problem for the strict-feedback nonlinear continuous systems involving input saturation and output constraints. A sequence of desired and auxiliary virtual control signals and real control input is designed to derive a representation of the system estimation errors and stabilize the system. The proposed approach is further developed via a finite-time stability theory, barrier Lyapunov function, and neural network approximation scheme to achieve an expected performance of the considered system. According to the proposed scheme, we solve the finite-time tracking control problem of the nonlinear systems with input saturation. Then, a theorem is provided to address that all the signals and system states are bounded, and the system output is driven to track the reference signal in a finite time to a small neighborhood of zero and remains in the predefined compact sets. The effectiveness of the proposed scheme is confirmed via two simulation examples.
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