Reversing Anticancer Drug Resistance by Synergistic Combination of Chemotherapeutics and Membranolytic Antitumor ß-Peptide Polymer.

Multidrug resistance is the main obstacle to cancer chemotherapy. Overexpression of drug efflux pumps causes excessive drug efflux from cancer cells, ultimately leading to drug resistance. Hereby, we raise an effective strategy to overcome multidrug resistance using a synergistic combination of membranolytic antitumor ß-peptide polymer and chemotherapy drugs. This membrane-active ß-peptide polymer promotes the transmembrane transport of chemotherapeutic drugs by increasing membrane permeability and enhances the activity of chemotherapy drugs against multidrug-resistant cancer cells. As a proof-of-concept demonstration, the synergistic combination of ß-peptide polymer and doxorubicin (DOX) is substantially more effective than DOX alone against drug-resistant cancer both in vitro and in vivo. Notably, the synergistic combination maintains a potent anticancer activity after continuous use. Collectively, this combination therapy using membrane lytic ß-peptide polymer appears to be an effective strategy to reverse anticancer drug resistance.

Facile Construction of Antimicrobial Surface via One-Step Co-Deposition of Peptide Polymer and Dopamine.

The infections associated with implantable medical devices can greatly affect the therapeutic effect and impose a heavy financial burden. Therefore, it is of great significance to develop antimicrobial biomaterials for the prevention and mitigation of healthcare-associated infections. Here, a facile construction of antimicrobial surface via one-step co-deposition of peptide polymer and dopamine is reported. The co-deposition of antimicrobial peptide polymer DLL60 BLG40 with dopamine (DA) on the surface of thermoplastic polyurethane (TPU) provides peptide polymer-modified TPU surface (TPU-DLL60 BLG40 ). The antimicrobial test shows that the TPU-DLL60 BLG40 surfaces of the sheet and the catheter both exhibit potent killing of 99.9% of methicillin-resistant Staphylococcus aureus (MRSA) and Escherichia coli (E. coli). In addition, the TPU-DLL60 BLG40 surface also exhibits excellent biocompatibility. This one-step antimicrobial modification method is fast and efficient, implies promising application in surface antimicrobial modification of implantable biomaterials and medical devices.

Deep Reinforcement Learning-Based Power Allocation for Minimizing Age of Information and Energy Consumption in Multi-Input Multi-Output and Non-Orthogonal Multiple Access Internet of Things Systems.

Multi-input multi-output and non-orthogonal multiple access (MIMO-NOMA) Internet-of-Things (IoT) systems can improve channel capacity and spectrum efficiency distinctly to support real-time applications. Age of information (AoI) plays a crucial role in real-time applications as it determines the timeliness of the extracted information. In MIMO-NOMA IoT systems, the base station (BS) determines the sample collection commands and allocates the transmit power for each IoT device. Each device determines whether to sample data according to the sample collection commands and adopts the allocated power to transmit the sampled data to the BS over the MIMO-NOMA channel. Afterwards, the BS employs the successive interference cancellation (SIC) technique to decode the signal of the data transmitted by each device. The sample collection commands and power allocation may affect the AoI and energy consumption of the system. Optimizing the sample collection commands and power allocation is essential for minimizing both AoI and energy consumption in MIMO-NOMA IoT systems. In this paper, we propose the optimal power allocation to achieve it based on deep reinforcement learning (DRL). Simulations have demonstrated that the optimal power allocation effectively achieves lower AoI and energy consumption compared to other algorithms. Overall, the reward is reduced by 6.44% and 11.78% compared the to GA algorithm and random algorithm, respectively.

Multimorbidity Analysis According to Sex and Age towards Cardiovascular Diseases of Adults in Northeast China.

Non-communicable diseases (NCDs) are great challenges in public health, where cardiovascular diseases (CVD) accounted for the large part of mortality that caused by NCDs. Multimorbidity is very common in NCDs especially in CVD, thus multimorbidity could make NCDs worse and bring heavy economic burden. This study aimed to explore the multimorbidity among adults, especially the important role of CVD that played in the entire multimorbidity networks. A total of 21435 participants aged 18-79 years old were recruited in Jilin province in 2012. Weighted networks were adopted to present the complex relationships of multimorbidity, and Charlson Comorbidity Index (CCI) was used to evaluate the burden of multimorbidity. The prevalence of CVD was 14.97%, where the prevalence in females was higher than that in males (P < 0.001), and the prevalences of CVD increased with age (from 2.22% to 38.38%). The prevalence of multimorbidity with CVD was 96.17%, and CVD could worsen the burden of multimorbidity. Multimorbidity and multimorbidity with CVD were more marked in females than those in males. And the prevalence of multimorbidity was the highest in the middle-age, while the prevalence of multimorbidity with CVD was the highest in the old population.