Controlled drug delivery systems in eradicating bacterial biofilm-associated infections

Drug delivery systems (DDS) have extensively progressed over the past decades for eradicating the bacteria embedded in biofilms while minimizing the side effects of antimicrobials on the normal tissues. They possess potential in solving the challenges of intrinsic antimicrobial-resistance and poor penetration of antimicrobials into biofilms. However, the guidelines for developing a controlled DDS for combating bacterial biofilms are limited. In this review, classical mechanisms and mathematical models of DDS were summarized in order to lay the foundation of controlled DDS development. Strategies for building controlled DDS were proposed based on the process of biofilm formation, including surface coatings, fibers, nanoparticles as DDS to prevent biofilm formation and eradicate bacterial biofilm-associated infections. The challenges that still remain in DDS design were discussed and future directions were suggested. We hope this review could give a "road map" to inspire readers and boost the development of the new generation of controlled drug release system for antimicrobial applications

Killing Two Birds with One Stone: Quantization Achieves Privacy in Distributed Learning

Communication efficiency and privacy protection are two critical issues in distributed machine learning. Existing methods tackle these two issues separately and may have a high implementation complexity that constrains their application in a resource-limited environment. We propose a comprehensive quantization-based solution that could simultaneously achieve communication efficiency and privacy protection, providing new insights into the correlated nature of communication and privacy. Specifically, we demonstrate the effectiveness of our proposed solutions in the distributed stochastic gradient descent (SGD) framework by adding binomial noise to the uniformly quantized gradients to reach the desired differential privacy level but with a minor sacrifice in communication efficiency. We theoretically capture the new trade-offs between communication, privacy, and learning performance

The Tradeoff Between Privacy and Accuracy in Anomaly Detection Using Federated XGBoost

Privacy has raised considerable concerns recently, especially with the advent of information explosion and numerous data mining techniques to explore the information inside large volumes of data. In this context, a new distributed learning paradigm termed federated learning becomes prominent recently to tackle the privacy issues in distributed learning, where only learning models will be transmitted from the distributed nodes to servers without revealing users' own data and hence protecting the privacy of users. In this paper, we propose a horizontal federated XGBoost algorithm to solve the federated anomaly detection problem, where the anomaly detection aims to identify abnormalities from extremely unbalanced datasets and can be considered as a special classification problem. Our proposed federated XGBoost algorithm incorporates data aggregation and sparse federated update processes to balance the tradeoff between privacy and learning performance. In particular, we introduce the virtual data sample by aggregating a group of users' data together at a single distributed node. We compute parameters based on these virtual data samples in the local nodes and aggregate the learning model in the central server. In the learning model upgrading process, we focus more on the wrongly classified data before in the virtual sample and hence to generate sparse learning model parameters. By carefully controlling the size of these groups of samples, we can achieve a tradeoff between privacy and learning performance. Our experimental results show the effectiveness of our proposed scheme by comparing with existing state-of-the-arts

From Knowing to Doing: Learning Diverse Motor Skills through Instruction Learning

Recent years have witnessed many successful trials in the robot learning field. For contact-rich robotic tasks, it is challenging to learn coordinated motor skills by reinforcement learning. Imitation learning solves this problem by using a mimic reward to encourage the robot to track a given reference trajectory. However, imitation learning is not so efficient and may constrain the learned motion. In this paper, we propose instruction learning, which is inspired by the human learning process and is highly efficient, flexible, and versatile for robot motion learning. Instead of using a reference signal in the reward, instruction learning applies a reference signal directly as a feedforward action, and it is combined with a feedback action learned by reinforcement learning to control the robot. Besides, we propose the action bounding technique and remove the mimic reward, which is shown to be crucial for efficient and flexible learning. We compare the performance of instruction learning with imitation learning, indicating that instruction learning can greatly speed up the training process and guarantee learning the desired motion correctly. The effectiveness of instruction learning is validated through a bunch of motion learning examples for a biped robot and a quadruped robot, where skills can be learned typically within several million steps. Besides, we also conduct sim-to-real transfer and online learning experiments on a real quadruped robot. Instruction learning has shown great merits and potential, making it a promising alternative for imitation learning

Status and Factors Associated with Healthcare Choices Among Older Adults and Children in an Urbanized County: A Cross-Sectional Study in Kunshan, China

As important unit for regional health planning, urbanized counties are facing challenges because of internal migrants and aging. This study took urbanized counties in China as cases and two key populations as objects to understand different populations’ intentions of choosing corresponding health service resources and to provide support for resource allocation. A cross-sectional study was conducted in Kunshan, a highly urbanized county in China, in 2016, among older adults aged 60 or over and children aged 0–6. Multinomial logistics models were used to identify the factors associated with healthcare choices. In this study, we found that income, distance of the tertiary provider, and migrant status were not associated with choices of tertiary healthcare outside county for children, while parents’ education level was. The responsiveness of the tertiary provider inside the county was lower than primary and secondary providers inside the county, while respondents were dissatisfied with the medical technology and medical facility for the tertiary inside the county compared to those of the tertiary provider outside the county. Significant differences existed in terms of the perception of different categories of institutions. To conclude, local governments should particularly seek to strengthen pediatric primary health services and improve the responsiveness of healthcare facilities to treat geriatric and pediatric diseases, which also bring significance to the developing countries in the process of urbanization

Intranasal Immunization with Recombinant HA and Mast Cell Activator C48/80 Elicits Protective Immunity against 2009 Pandemic H1N1 Influenza in Mice

Pandemic influenza represents a major threat to global health. Vaccination is the most economic and effective strategy to control influenza pandemic. Conventional vaccine approach, despite being effective, has a number of major deficiencies including limited range of protection, total dependence on embryonated eggs for production, and time consuming for vaccine production. There is an urgent need to develop novel vaccine strategies to overcome these deficiencies.The major objective of this work was to develop a novel vaccine strategy combining recombinant haemagglutinin (HA) protein and a master cell (MC) activator C48/80 for intranasal immunization. We demonstrated in BALB/c mice that MC activator C48/80 had strong adjuvant activity when co-administered with recombinant HA protein intranasally. Vaccination with C48/80 significantly increased the serum IgG and mucosal surface IgA antibody responses against HA protein. Such increases correlated with stronger and durable neutralizing antibody activities, offering protection to vaccinated animals from disease progression after challenge with lethal dose of A/California/04/2009 live virus. Furthermore, protected animals demonstrated significant reduction in lung virus titers, minimal structural alteration in lung tissues as well as higher and balanced production of Th1 and Th2 cytokines in the stimulated splenocytes when compared to those without C48/80.The present study demonstrates that the novel vaccine approach of combining recombinant HA and mucosal adjuvant C48/80 is safe and effective in eliciting protective immunity in mice. Future studies on the mechanism of action of C48/80 and potential combination with other vaccine strategies such as prime and boost approach may help to induce even more potent and broad immune responses against viruses from various clades

The Effectiveness of an eHealth Family-Based Intervention Program in Patients With Uncontrolled Type 2 Diabetes Mellitus (T2DM) in the Community Via WeChat: Randomized Controlled Trial

Background: Intervention based on family support and risk perception can enhance type 2 diabetes mellitus (T2DM) patients’ self-care activities. In addition, eHealth education is considered to improve family members’ support for patients with T2DM. However, there is little evidence from rigorously designed studies on the effectiveness of an intervention combining these approaches. Objective: This randomized controlled trial (RCT) aimed to assess the effectiveness of an eHealth family-based health education intervention for patients with T2DM to improve their glucose control, risk perception, and self-care behaviors. Methods: This single-center, 2-parallel-group RCT was conducted between 2019 and 2020. Overall, 228 patients were recruited from Jiading District, Shanghai, and randomly divided into intervention and control groups. The intervention group received an eHealth family intervention based on community management via WeChat, whereas the control group received usual care. The primary outcome was the glycated hemoglobin (HbA1c) level of the patients with T2DM, and the secondary outcomes were self-management behavior (general and specific diet, exercise, blood sugar testing, foot care, and smoking), risk perception (risk knowledge, personal control, worry, optimism bias, and personal risk), and family support (supportive and nonsupportive behaviors). A 2-tailed paired-sample t test was used to compare the participants at baseline and follow-up within the control and intervention groups. An analysis of covariance was used to measure the intervention effect. Results: In total, 225 patients with T2DM were followed up for 1 year. After intervention, they had significantly lower HbA1c values (β=–.69, 95% CI –0.99 to –0.39; PP=.003), special diet (β=.71, 95% CI 0.34 to 1.09; PP=.04), foot care (β=1.82, 95% CI 1.23 to 2.42; PPPP=.001), optimism bias (β=.26, 95% CI 0.09 to 0.43; P=.003), and supportive behaviors (β=5.52, 95% CI 4.03 to 7.01; P\u3c.001). Conclusions: The eHealth family-based intervention improved glucose control and self-care activities among patients with T2DM by aiding the implementation of interventions to improve T2DM risk perceptions among family members. The intervention is generalizable for patients with T2DM using health management systems in community health centers. Trial Registration: Chinese Clinical Trial Registry ChiCTR1900020736; https://www.chictr.org.cn/showprojen.aspx?proj=3121

Applications and Perspectives of Cascade Reactions in Bacterial Infection Control

Cascade reactions integrate two or more reactions, of which each subsequent reaction can only start when the previous reaction step is completed. Employing natural substrates in the human body such as glucose and oxygen, cascade reactions can generate reactive oxygen species (ROS) to kill tumor cells, but cascade reactions may also have potential as a direly needed, novel bacterial infection-control strategy. ROS can disintegrate the EPS matrix of infectious biofilm, disrupt bacterial cell membranes, and damage intra-cellular DNA. Application of cascade reactions producing ROS as a new infection-control strategy is still in its infancy. The main advantages for infection-control cascade reactions include the fact that they are non-antibiotic based and induction of ROS resistance is unlikely. However, the amount of ROS generated is generally low and antimicrobial efficacies reported are still far <3-4 log units necessary for clinical efficacy. Increasing the amounts of ROS generated by adding more substrate bears the risk of collateral damage to tissue surrounding an infection site. Collateral tissue damage upon increasing substrate concentrations may be prevented by locally increasing substrate concentrations, for instance, using smart nanocarriers. Smart, pH-responsive nanocarriers can self-target and accumulate in infectious biofilms from the blood circulation to confine ROS production inside the biofilm to yield long-term presence of ROS, despite the short lifetime (nanoseconds) of individual ROS molecules. Increasing bacterial killing efficacies using cascade reaction components containing nanocarriers constitutes a first, major challenge in the development of infection-control cascade reactions. Nevertheless, their use in combination with clinical antibiotic treatment may already yield synergistic effects, but this remains to be established for cascade reactions. Furthermore, specific patient groups possessing elevated levels of endogenous substrate (for instance, diabetic or cancer patients) may benefit from the use of cascade reaction components containing nanocarriers