Bacterial biofilms can make traditional antibiotics impenetrable and even promote the development of antibiotic-resistant strains. Therefore, non-antibiotic strategies to effectively penetrate and eradicate the formed biofilms are urgently needed. Here, we demonstrate the development of self-propelled biohybrid microrobots that can enhance the degradation and penetration effects for Pseudomonas aeruginosa biofilms in minimally invasive strategy. The biohybrid microrobots (CR@Alg) are constructed by surface modification of Chlamydomonas reinhardtii (CR) microalgae with alginate lyase (Alg) via biological orthogonal reaction. By degrading the biofilm components, the number of CR@Alg microrobots with fast-moving capability penetrating the biofilm increases by around 2.4-fold compared to that of microalgae. Massive reactive oxygen species are subsequently generated under laser irradiation due to the presence of chlorophyll, inherent photosensitizers of microalgae, thus triggering photodynamic therapy (PDT) to combat bacteria. Our algae-based microrobots with superior biocompatibility eliminate biofilm-infections efficiently and tend to suppress the inflammatory response in vivo, showing huge promise for the active treatment of biofilm-associated infections.

Objective To investigate risk factors of medication non-adherence in elderly patients with hypertension through Meta-analysis.Methods Literatures on medication non-adherence in elderly patients with hypertension were systematically reviewed across various databases,from inception to September 1st 2023,including CNKI,VIP,Wangfong Database,SinoMed,PubMed,Web of Science,Cochrane Library、EMbase.Meta-analysis was conducted using RevMan 5.4.Results A total of 19 articles were included,comprising a total of 18 220 patients in sample size.Meta analysis identified 10 risk factors,showed significant association(P<0.05)with:age[OR=1.36,95%CI=(1.00,1.86)],place of residence[OR=1.91,95%CI=(1.33,2.75)],method of payment for medical expenses[OR=1.60,95%CI=(1.38,1.86)],income level[OR=1.68,95%CI=(1.45,1.95)],occupational status[OR=1.79,95%CI=(1.37,2.36)],social support[OR=1.43,95%CI=(1.27,1.60)],comorbidity[CI=0.33,95%(0.19,0.58)],frequency of blood pressure measurement[CI=1.53,95%(1.14,2.05)],disease awareness[OR=1.70,95%CI=(1.44,2.00)]and dedication frequency[OR=1.44,95%CI=(1.16,1.79)].In addition,the number of influencing factors such as gender,marital status,depression,cognitive impairment,and complications was included in<3 articles,and only descriptive analysis was conducted.Conclusion Healthcare providers should focus on the identification and management of the risk factors associated with medication non-adherence in elderly patients with hypertension,therefore to reduce the incidence of medication non-adherence.

Objective: To construct and implement a calculation model of clinical nursing post classification. Methods: Between October to December 2018, head nurses of the hospital were screened as consultants, and Delphi method was used to determine the indicators, while the weights were assigned from the aspects of nursing workload, work quality, patient satisfaction and number of nursing night shifts. Combined with HIS data, the calculation model of clinical nursing post classification was constructed to classify clinical nursing units into different categories and levels. Results: After two rounds of expert enquiry, 82 nursing work items were identified and the objective weight assignment was determined ranging from 0.80 to16.14. According to the established calculation model and HIS data, nursing posts in clinical departments were classified into 6 levels and 3 categories, and the accurate management of clinical nursing post classification was achieved. Conclusions The construction of a calculation model is scientific and rigorous, which provides a scientific basis for dynamic nurse performance management and rational allocation of human resources. In addition, it provides a useful reference for accurate nursing management.