Acute liver failure (ALF) is a life-threatening condition associated with macrophage-mediated inflammatory responses. Effective therapies and drugs are still lacking to date. Here, we reveal that a derivative of xanthohumol, CAM12203, alleviates lipopolysaccharide (LPS) + d-galactosamine (D-GalN)-induced ALF through limiting macrophage-mediated inflammation, with the most significant impact on interleukin-1β (IL-1β) transcription. Through biotin labeling-mediated pull-down and LC-MS/MS analysis, diacylglycerol kinase ζ (DGKζ), a lipid-metabolizing kinase, is identified as the direct target of CAM12203. Mechanistically, DGKζ is induced in macrophages upon inflammatory stimuli and is upregulated observed on clinical liver failure samples. Its product phosphatidic acid (PA) boosts phospholipase C (PLC)-inositol 1,4,5-trisphosphate (IP₃)-Ca²⁺ signaling and subsequent janus kinase 2 (JAK2)-signal transducer and activator of transcription 3 (STAT3) cascade, ultimately promoting IL-1β production and liver failure. DGKζ knockdown/ablation or inhibition significantly impairs the DGKζ-STAT3-IL-1β pathway along with ALF progression. Finally, CAM12203 is confirmed to be a new DGKζ inhibitor and acts against inflammation in a DGKζ-reliant manner. Taken together, CAM12203 inhibits IL-1β transcription in macrophages by binding to DGKζ and blocking the DGKζ-STAT3 axis, thereby exerting an ameliorative effect on ALF. These results not only highlight CAM12203 as a promising lead compound for ALF treatment, but also define DGKζ as a novel therapeutic target.

Objective:To construct a predictive model to assess the risk of severe respiratory syncytial virus infection among children under five years in China, conduct preliminary validation of this model by using external data, and develop an individual risk assessment tool available for their parents.Methods:The admission after RSV infection was used as a marker of severe infection. Based on the evidence of RSV hospitalization-related risk factors and real-world data, such as the prevalence of various risk factors in children under five years old in China, a Monte Carlo-based individual RSV hospitalization risk prediction model for children under five years old was constructed. Taking Suzhou City as an example, the model was externally validated, and an interactive risk prediction tool (RSV HeaRT) was developed on the WeChat mini-program platform.Results:The estimation model showed that in children under five years old in China if the population did not have any risk factors for severe RSV infection, the RSV annual hospitalization rate was 2.2/1 000 (95% CI: 0.9/1 000-7.5/1 000). Based on this baseline hospitalization rate and the prevalence of related risk factors in Suzhou, the model predicted an RSV hospitalization rate of 8.0/1 000 (95% CI: 4.6/1 000-24.4/1 000) for children under five years old annually in Suzhou, which was close to the reported RSV hospitalization rate in literature (10/1 000-20/1 000). In the developed RSV HeaRT WeChat mini-program, target users (such as parents of children) could input basic information, disease history, and social environmental factors of the child into the mini-program, and the tool could provide real-time feedback on the following predicted results: First, the relative risk of hospitalization due to RSV infection in current children compared to general children; Second, the probability of hospitalization due to RSV infection within the next year; Third, the relative risk of adverse outcomes during hospitalization in the event of RSV infection. Conclusion:This study is based on real-world evidence related to RSV hospitalization risk and constructs an RSV hospitalization risk prediction model suitable for Chinese children based on the combination of the current prevalence of risk factors in children under five years old in China. The accuracy of the prediction model results has been preliminarily demonstrated. Based on this design, the RSV HeaRT developed can facilitate parents to evaluate the hospitalization risk of children.

Objective:To construct a predictive model to assess the risk of severe respiratory syncytial virus infection among children under five years in China, conduct preliminary validation of this model by using external data, and develop an individual risk assessment tool available for their parents.Methods:The admission after RSV infection was used as a marker of severe infection. Based on the evidence of RSV hospitalization-related risk factors and real-world data, such as the prevalence of various risk factors in children under five years old in China, a Monte Carlo-based individual RSV hospitalization risk prediction model for children under five years old was constructed. Taking Suzhou City as an example, the model was externally validated, and an interactive risk prediction tool (RSV HeaRT) was developed on the WeChat mini-program platform.Results:The estimation model showed that in children under five years old in China if the population did not have any risk factors for severe RSV infection, the RSV annual hospitalization rate was 2.2/1 000 (95% CI: 0.9/1 000-7.5/1 000). Based on this baseline hospitalization rate and the prevalence of related risk factors in Suzhou, the model predicted an RSV hospitalization rate of 8.0/1 000 (95% CI: 4.6/1 000-24.4/1 000) for children under five years old annually in Suzhou, which was close to the reported RSV hospitalization rate in literature (10/1 000-20/1 000). In the developed RSV HeaRT WeChat mini-program, target users (such as parents of children) could input basic information, disease history, and social environmental factors of the child into the mini-program, and the tool could provide real-time feedback on the following predicted results: First, the relative risk of hospitalization due to RSV infection in current children compared to general children; Second, the probability of hospitalization due to RSV infection within the next year; Third, the relative risk of adverse outcomes during hospitalization in the event of RSV infection. Conclusion:This study is based on real-world evidence related to RSV hospitalization risk and constructs an RSV hospitalization risk prediction model suitable for Chinese children based on the combination of the current prevalence of risk factors in children under five years old in China. The accuracy of the prediction model results has been preliminarily demonstrated. Based on this design, the RSV HeaRT developed can facilitate parents to evaluate the hospitalization risk of children.

Objective To investigate the status of health knowledge of patients after percutaneous coronary intervention (PCI) and its influencing factors, so as to provide a scientific basis for formulating targeted health education programs. Methods Using a self-designed questionnaire on health cognition after PCI, 433 patients with a history of PCI surgery at a Grade III, Class A hospital between January 2019 and December 2019 were selected as the research subjects to investigate their health cognition and the influencing factors by binary logistic regression analysis. Results The pass rate of health cognition of patients after PCI was 39%, and the total correct rate was 57.5%. The correct rate of drug knowledge and risk factors was the lowest (33.6% and 48.5%, respectively). Binary logistic regression showed that gender, age and cardiac function classification were risk factors for health cognition of patients after PCI, while education level, occupation category and recurrence of discomfort after PCI were protective factors. Conclusion The level of health cognition of patients after PCI is low. Gender, age, education level, occupation category, cardiac function classification and recurrence of discomfort after PCI are independent influencing factors. When implementing health education, medical staff should comprehensively consider the formulation of individualized health education to help.

Objective:To study the clustered regularly interspaced short palindromic repeats (CRISPR) loci polymorphism of Yersinia pestis and its area distribution in Gansu province. Methods:A total of 203 strains of Yersinia pestis isolated from 1962 to 2014 were selected for the culture and extraction of DNA. Three pairs of CRISPR primers were used to amplify the strain DNA by PCR, and the PCR products were sequenced. The groups and genotypes of strains were determined according to the spacer and spacer arrangement of CRISPR loci in the strain. Cluster analysis was done by using the software BioNumerics 5.10. Results:A total of 16 spacers, including 9 species of YPa loci, 4 species of YPb loci and 3 species of YPc loci, were found in the 203 strains of Yersinia pestis. A new spacer of a1′ was found. The 203 strains were divided into 5 CRISPR genotypes and classified into 5 CRISPR clusters (Cb2, Ca7, Ca7′, CaΔ5′ and Ca35′). Each cluster showed significant area-specific characteristics, Cb2 was mainly distributed in Huining country and Pingchuan district, Ca7 was mainly found in Aksai Kazak autonomous country, Ca7′ was mainly found in Xiahe country, Ca35′ was mainly found in Subei Mongolia autonomous county and Yumen city and CaΔ5′ was mainly distributed in Sunan Yugur autonomous county. Conclusions:The strains from different plague foci in Gansu were distinguished by CRISPR, all kinds of clusters showed the obvious area specific characteristics. It is important to study the evolution of Yersinia pestis in Gansu and trace the molecular biology origin of human plague.