Zinc-induced inhibition of protein synthesis and reduction of connexin-43 expression and intercellular communication in mouse cortical astrocytes

Restoring Homeostasis: Treating Amyotrophic Lateral Sclerosis by Resolving Dynamic Regulatory Instability

Amyotrophic lateral sclerosis (ALS) has an interactive, multifactorial etiology that makes treatment success elusive. This study evaluates how regulatory dynamics impact disease progression and treatment. Computational models of wild-type (WT) and transgenic SOD1-G93A mouse physiology dynamics were built using the first-principles-based first-order feedback framework of dynamic meta-analysis with parameter optimization. Two in silico models were developed: a WT mouse model to simulate normal homeostasis and a SOD1-G93A ALS model to simulate ALS pathology dynamics and their response to in silico treatments. The model simulates functional molecular mechanisms for apoptosis, metal chelation, energetics, excitotoxicity, inflammation, oxidative stress, and proteomics using curated data from published SOD1-G93A mouse experiments. Temporal disease progression measures (rotarod, grip strength, body weight) were used for validation. Results illustrate that untreated SOD1-G93A ALS dynamics cannot maintain homeostasis due to a mathematical oscillating instability as determined by eigenvalue analysis. The onset and magnitude of homeostatic instability corresponded to disease onset and progression. Oscillations were associated with high feedback gain due to hypervigilant regulation. Multiple combination treatments stabilized the SOD1-G93A ALS mouse dynamics to near-normal WT homeostasis. However, treatment timing and effect size were critical to stabilization corresponding to therapeutic success. The dynamics-based approach redefines therapeutic strategies by emphasizing the restoration of homeostasis through precisely timed and stabilizing combination therapies, presenting a promising framework for application to other multifactorial neurodegenerative diseases.

ZIP1+ fibroblasts protect lung cancer against chemotherapy via connexin-43 mediated intercellular Zn2+ transfer

Tumour-stroma cell interactions impact cancer progression and therapy responses. Intercellular communication between fibroblasts and cancer cells using various soluble mediators has often been reported. In this study, we find that a zinc-transporter (ZIP1) positive tumour-associated fibroblast subset is enriched after chemotherapy and directly interconnects lung cancer cells with gap junctions. Using single-cell RNA sequencing, we identify several fibroblast subpopulations, among which Zip1+ fibroblasts are highly enriched in mouse lung tumours after doxorubicin treatment. ZIP1 expression on fibroblasts enhances gap junction formation in cancer cells by upregulating connexin-43. Acting as a Zn2+ reservoir, ZIP1+ fibroblasts absorb and transfer Zn2+ to cancer cells, leading to ABCB1-mediated chemoresistance. Clinically, ZIP1high stromal fibroblasts are also associated with chemoresistance in human lung cancers. Taken together, our results reveal a mechanism by which fibroblasts interact directly with tumour cells via gap junctions and contribute to chemoresistance in lung cancer.

Identification of drug side effects with a path-based method

The study of drug side effects is a significant task in drug discovery. Candidate drugs with unaccepted side effects must be eliminated to prevent risks for both patients and pharmaceutical companies. Thus, all side effects for any candidate drug should be determined. However, this task, which is carried out through traditional experiments, is time-consuming and expensive. Building computational methods has been increasingly used for the identification of drug side effects. In the present study, a new path-based method was proposed to determine drug side effects. A heterogeneous network was built to perform such method, which defined drugs and side effects as nodes. For any drug and side effect, the proposed path-based method determined all paths with limited length that connects them and further evaluated the association between them based on these paths. The strong association indicates that the drug has a side effect with a high probability. By using two types of jackknife test, the method yielded good performance and was superior to some other network-based methods. Furthermore, the effects of one parameter in the method and heterogeneous network was analyzed.

Effect of Zinc Supplementation on Maintenance Hemodialysis Patients: A Systematic Review and Meta-Analysis of 15 Randomized Controlled Trials

We aimed to examine the effects of zinc supplementation on nutritional status, lipid profile, and antioxidant and anti-inflammatory therapies in maintenance hemodialysis (MHD) patients. We performed a systematic review and meta-analysis of randomized, controlled clinical trials of zinc supplementation. Metaregression analyses were utilized to determine the cause of discrepancy. Begg and Egger tests were performed to assess publication bias. Subgroup analysis was utilized to investigate the effects of zinc supplementation in certain conditions. In the crude pooled results, we found that zinc supplementation resulted in higher serum zinc levels (weighted mean difference [WMD] = 28.489; P < 0.001), higher dietary protein intake (WMD = 8.012; P < 0.001), higher superoxide dismutase levels (WMD = 357.568; P = 0.001), and lower levels of C-reactive protein (WMD = −8.618; P = 0.015) and malondialdehyde (WMD = −1.275; P < 0.001). The results showed no differences in lipid profile. In the metaregression analysis, we found that serum zinc levels correlated positively with intervention time (β = 0.272; P = 0.042) and varied greatly by ethnicity (P = 0.023). Results from Begg and Egger tests showed that there was no significant bias in our meta-analysis (P > 0.1). Results of subgroup analysis supported the above results. Our analysis shows that zinc supplementation may benefit the nutritional status of MHD patients and show a time-effect relationship.