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Background: Resistance to oxaliplatin (L-OHP) is a major barrier in the treatment of colorectal cancer (CRC). Autophagy is the main cause of L-OHP tolerance in CRC cells. Method: The human colon cancer cell lines HCT116 and SW480 were treated with L-OHP to obtain the drug-resistant cell lines HCT116/L-OHP and SW480/L-OHP, respectively. To probe the relationship between autophagy and L-OHP tolerance of growth factor independent 1 (Gfi-1) and high-mobility group protein 1 (HMGB1) in CRC cells, gene knockout or overexpression was performed, and Western blotting was used to determine the levels of drug tolerance interrelated proteins. Transwell and CCK-8 assays were employed to analyze the proliferation of cancer cells. Immunofluorescence detection of LC3 reflected autophagy levels. Finally, the relationship between Gfi-1 and HMGB1 was detected by chromatin immunoprecipitation (ChIP). Result: Compared to normal CRC cells, L-OHP-tolerant CRC cells exhibited greater autophagy (8.2 times greater in HCT116/L-OHP cells and 7.4 times greater in SW480/L-OHP cells). In addition, we detected low levels of Gfi-1 (0.6-fold for HCT116/L-OHP cells and 0.4-fold for SW480/L-OHP cells), and OE-Gfi-1 decreased HMGB1 levels (0.6-fold for HCT116/L-OHP + OE-Gfi-1 cells and 0.5-fold for SW480/L-OHP + OE-Gfi-1 cells). The inhibition of Gfi-1 further enhanced cell viability (1.7 times in HCT116+sh-Gfi-1 cells and 1.2 times in SW480+sh-Gfi-1 cells) and invasion (1.8 times in HCT116+sh-Gfi-1 cells and 2.1 times in SW480+sh-Gfi-1 cells) in CRC cells, thus promoting oxaliplatin resistance in these cells. The autophagy inhibitor 3-MA reversed the above effects. Furthermore, we noted that Gfi-1 can restrain HMGB1 expression by binding to its promoter (0.5 times in HCT116+OE-Gfi-1 cells and 0.5 times in SW480+OE-Gfi-1 cells). The inhibitory influence of 3-MA on HMGB1 reversed the influence of Gfi-1 on autophagy and malignant progression in CRC cells. Conclusion: Our study suggested that Gfi-1 inhibited HMGB1 to reduce CRC autophagy levels, increasing CRC sensitivity to L-OHP.
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Introduction: Falls, which have a higher incidence and mortality due to accidental injuries, are a major global health challenge. The effects of lifestyle factor, health indicator, psychological condition, and functional status interventions on the risk of falls are unknown and the conventional regression model would not adjust for the confounders. This study aimed to evaluate the 4-year risk of falls on the basis of these hypothetical interventions among Chinese older adults. Methods: Data were obtained from 9,692 aged 65 years and over older adults in the China Health and Retirement Longitudinal Study wave, from 2011 to 2015. We used the parametric g-formula to evaluate the risk of falls on the basis of independent hypothetical interventions of sleep duration, social activities, smoking status, drinking status, body mass index (BMI), systolic blood pressure (SBP), vision, depression, activities of daily living (ADL), and their different joint intervention combinations. Results: During the follow-up of 4 years, we documented 1,569 falls. The observed risk of falls was 23.58%. The risk ratios (95% confidence intervals [CIs]) of falls under the intensive hypothetical interventions on increasing sleep duration, participating in more social activities, quit smoking and drinking, reducing BMI and SBP, better vision, alleviating depressive symptoms, and improving ADL capability were 0.93 (0.87-0.96), 0.88 (0.79-0.92), 0.98 (0.95-1.03), 0.97 (0.95-1.02), 0.92 (0.86-1.03), 0.93 (0.87-1.04), 0.86 (0.74-0.91), 0.91 (0.85-0.96), and 0.79 (0.74-0.85), respectively. The feasible and intensive joint hypothetical intervention reduced the 4-year fall risk by 22% (95% CI: 0.52-0.91) and 33% (95% CI: 0.56-0.72), respectively. Conclusions: Hypothetical interventions for increasing sleep duration, participating in more social activities, better vision, alleviating depressive symptoms, and improving ADL capability help protect older adults from falls. Our findings suggest that a combination of lifestyle factors, health indicators, psychological conditions, and functional status may prove to be an effective strategy for preventing falls among older adults.