Isolation and characterizations of multidrug-resistant human cancer cells by a biodegradable nano-sensor.

Multidrug resistance (MDR) remains a significant challenge in cancer therapy, with inherent and acquired resistance distinct. While conventional drug selection processes enable the isolation of cancer cells with acquired multidrug resistance, identifying cancer cells with inherent drug resistance remains challenging. Herein, we proposed a molecular beacon (MB)-based strategy to identify and isolate the inherent MDR cancer cells. A lipid/PLGA core-shell nanoparticulate system (DNCP) was designed to deliver MB for intracellular MDR1 mRNA imaging. DNCP-MB - possess a surface potential of -8 mV and a size of 150 nm - demonstrated effective delivery of MB, remarkable selectivity towards the selected intracellular mRNA targets, and low cytotoxicity. Following DNCP transfection, fluorescence-activated cell sorting (FACS) was employed to differentiate MCF-7 cells into two distinct sub-populations: the Top 10 cells with a high level of MDR gene expression and the Bottom 10 cells with a low level of MDR gene expression, which represent inherent drug-resistant and non-drug-resistant cells, respectively. Intriguingly, we observed a positive correlation between elevated MDR1 mRNA expression and increased migration, enhanced proliferation rate, and tighter spheroid formation. Moreover, we conducted RNA sequencing analysis on the Top 10, Bottom 10, and MCF-7/ADR cells. The findings revealed a notable disparity in the gene ontology enrichment analysis of differentially expressed genes between the Top 10 and Bottom 10 cells when compared to the Bottom 10 and MCF-7/ADR cells. This novel approach provides a promising avenue for isolating inherent drug-resistant cells and holds significant potential in unraveling the mechanisms underlying inherent drug resistance.

The association of dietary resistance starch intake with all-cause and cause-specific mortality.

Background: Several studies have estimated daily intake of resistant starch (RS), but no studies have investigated the relationship of RS intake with mortality. Objective: We aimed to examine associations between RS intake and all-cause and cause-specific mortality. Methods: Data from US National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 with 24-h dietary recall data was used in current study. The main exposure in this study was RS intake, and the main outcome was the mortality status of participants until December 31, 2019. The multivariable Cox proportional hazards regression models were developed to evaluate the hazard ratios (HRs) and 95% confidence interval (95% CI) of cardiovascular disease (CVD), cancer, and all-cause mortality associated with RS intake. Results: A total of 42,586 US adults [mean (SD) age, 46.91 (16.88) years; 22,328 (52.43%) female] were included in the present analysis. During the 454,252 person-years of follow-up, 7,043 all-cause deaths occurred, including 1,809 deaths from CVD and 1,574 deaths from cancer. The multivariable-adjusted HRs for CVD, cancer, and all-cause mortality per quintile increase in RS intake were 1 (95%CI, 0.97-1.04), 0.96 (95%CI, 0.93-1), and 0.96 (95%CI, 0.95-0.98), respectively. The associations remained similar in the subgroup and sensitivity analyses. Conclusion: Higher RS intake is significantly associated with lower cancer and all-cause mortality, but not significantly with CVD mortality. Future studies focusing on other populations with different food sources of RS and RS subtypes are needed to access the dose-response relationship and to improve global dietary recommendations.

Analysis of Legal Issues of Personal Information Protection in the Field of Big Data.

In the era of big data, while every citizen enjoys the convenience of the Internet, all kinds of information closely related to their personal and property are in a state of "streaking" for a long time. Personal information is frequently leaked, illegally misappropriated, and used. There are necessary requirements of network security. The risks and challenges faced by personal information in the context of big data increase. In the context of the rapid development of big data, the information is circulated in virtual cyberspace in the form of electronic data, and data sharing has become an important flow form of information circulation. It is an important link to realize the optimal allocation of network resources and realize the value of data. The great progress of the digital economy and artificial intelligence technology has greatly increased the demand for data, the speed of circulation has been further accelerated, and the potential value of data has been fully reflected. At present, the scope of personal information protected by Chinese laws is relatively narrow and is basically limited to the scope of privacy rights, which makes a large amount of information owned by individuals that do not belong to the category of personal privacy rights lack legal protection. Personal information is different from the characteristics of privacy rights. It is decided that the protection of personal information should be different from the protection of traditional personal privacy. To sum up, in view of this, this article attempts to analyze the new challenges faced by personal information protection in the era of big data from the perspective of law, combined with the background of the era of big data, from the legislative model, system design, supervision mechanism, industry self-discipline, and other aspects. Exploration of the legislative framework for the protection of personal information in the era of big data in our country is done in order to find a realistic path that balances the development of big data technology and the protection of personal information.