Objective: To investigate the effect of integrin α5 on the expression of NOD-like receptor thermal protein domain associated protein 3 (NLRP3) in periodontal ligament fibroblasts (PDLFs) within an inflammatory microenvironment. Methods: This study was approved by the Ethics Committee of Laboratory animals. After rat PDLFs were treated with LPS (0.5, 5, and 50 µg/mL) for 24 h, the primary medium was discarded and replaced with serum-free culture medium. After 24 h, the supernatant was collected and mixed with DMEM medium containing 10% exosome-free serum at a volume ratio of 1:1 to obtain conditioned medium (CM). The groups were labeled as the 0.5-CM, 5-CM, and 50-CM groups. In addition, PDLFs cultured in DMEM medium containing 10% exosome-free serum were considered the 0-CM group. PDLFs were cultured with the above CM. In the inhibitor group, PDLFs were cultured in 0-CM containing different concentrations of integrin α5 inhibitor ATN-161 (0, 0.025, 0.25, 2.5, 25, and 250 μg/mL). The effect of CM and integrin α5 inhibitor ATN-161 on cell viability was assessed using the CCK-8 assay. According to the CCK-8 results, in further inhibitor intervention experiments, PDLFs were cultured in 0-CM, 5-CM (without/with 25 μg/mL ATN-161), and 0-CM containing 25 μg/mL ATN-161, which were labeled as the 0-CM, 5-CM, ATN-161+5-CM, and ATN-161 groups, respectively. The expression changes of integrin α5 and NLRP3 were detected using Western blot and qRT-PCR techniques. For in vivo experiments, 24 rats were randomly divided into four groups (n=6). The control group contained healthy rats that received no treatment. The rats in the other three groups were injected with 40 µL of 0-CM containing 25 μg/mL ATN-161 or 5-CM (without or with 25 μg/mL ATN-161) on the palatal side of the left maxillary first molar every three days; these groups were classified as the ATN-161, 5-CM, and ATN-161+5-CM groups, respectively. On the 30th day, the left maxillary tissue of rats was used for Micro-CT, HE staining, and immunohistochemical detection. Results : The CCK-8 assay showed that CM, 25 μg/mL ATN-161, and ATN-161 concentrations below 25 μg/mL had no significant effect on cell viability at 12 h and 24 h (P > 0.05). 50-CM and 25 μg/mL ATN-161 significantly inhibited cell viability at 48 h (P < 0.05). For in vitro experiments, compared to the 0-CM group, both the protein and mRNA levels of integrin α5 and NLRP3 were significantly increased in rat PDLFs in the 5-CM group (P < 0.05). Intervention with 25 μg/mL ATN-161 significantly attenuated the enhancement of 5-CM on the expression of integrin α5 and NLRP3 (P < 0.05). For in vivo experiments, compared to the control group, alveolar bone resorption and periodontal inflammatory cell infiltration were significantly increased in the 5-CM and ATN-161+5-CM groups, and the expression of integrin α5 and NLRP3 was significantly increased (P < 0.01). However, compared to the 5-CM group, the ATN-161+5-CM group had less alveolar bone resorption and fewer periodontal inflammatory cells. Further, the expression of integrin α5 and NLRP3 was significantly reduced (P < 0.01). Conclusion In vitro and in vivo experiments showed that integrin α5 mediated NLRP3 expression in PDLFs under an inflammatory microenvironment. ATN-161 inhibited the expression of integrin α5, thus significantly downregulating the expression of NLRP3, which plays a role in inhibiting inflammation.

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.