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Summary: Background: Checkpoint inhibitor pneumonitis (CIP) is a potentially fatal adverse event characterized by new pulmonary infiltrates in cancer patients receiving immune checkpoint inhibitor therapy. This study aims to explore the interplay between lung microbiota, dysregulated metabolites, and host immunity in CIP. Methods: We recruited thirteen hospitalized CIP patients, eleven idiopathic pulmonary fibrosis (IPF) patients, and ten new-onset non-small cell lung cancer patients. Bronchoalveolar lavage fluid samples were collected for 16S rRNA gene sequencing. The percentages of immune cells were determined using manual counting and flow cytometry. Interactions among microbiota, metabolites, and lymphocytes were analyzed using cultured mouse splenocytes and human T cells. Findings: Proteobacteria emerged as the dominant phylum, notably abundant in both the CIP and IPF groups. Vibrio, Halomonas, Mangrovibacter, and Salinivibrio were the predominant microbiota because of their discriminative abundance patterns. Vibrio (r = 0.72, P-adj = 0.007) and Halomonas (r = 0.65, P-adj = 0.023) demonstrated strong correlations with lymphocytes. Vibrio metschnikovii and Mangrovibacter plantisponsors were more abundant in the CIP group than in the IPF group. Lauroylcarnitine, a key intermediary metabolite co-occurring with the predominant microbiota, exhibited a potent effect on cytokine secretion by mouse and human T cells, notably enhancing IFN-γ and TNF-α production from CD4 and CD8 cells in vitro. Interpretation: Lauroylcarnitine, co-occurring with the predominant lung microbiota in CIP, could activate T cells in vitro. These findings suggest potential involvement of lung microbiota and acylcarnitine metabolism dysregulation in the pathogenesis of CIP. Funding: This work was supported by Peking University People’s Hospital Scientific Research Development Funds (RDJ2022-15) and Provincial Key Clinical Specialty Capacity Building Project 2020 (Department of the Respiratory Medicine).

BackgroundIdentifying the diagnosis as well as prognosis for patients presented with community-acquired pneumonia (CAP) remains challenging. We aimed to identify the role of lysophosphatidylcholine acyl-transferase (LPCAT) for CAP along with assessing this protein’s effectiveness as a biomarker for severity of disease and mortality.MethodsProspective multicenter research study was carried out among hospitalized patients. A total of 299 CAP patients (including 97 severe CAP patients [SCAP]) and 20 healthy controls (HC) were included. A quantitative enzyme-linked immunosorbent test kit was employed for detecting the LPCAT level in plasma. We developed a deep-learning-based binary classification (SCAP or non-severe CAP [NSCAP]) model to process LPCAT levels and other laboratory test results.ResultsThe level of LPCAT in patients with SCAP and death outcome was significantly higher than that in other patients. LPCAT showed the highest predictive value for SCAP. LPCAT was able to predict 30-day mortality among CAP patients, combining LPCAT values with PSI scores or CURB-65 further enhance mortality prediction accuracy.ConclusionThe on admission level of LPCAT found significantly raised among SCAP patients and strongly predicted SCAP patients but with no correlation to etiology. Combining the LPCAT value with CURB-65 or PSI improved the 30-day mortality forecast significantly.Trial registrationNCT03093220 Registered on March 28th, 2017.

Background: Both socially regulated learning and cognitive quality are important factors affecting collaborative knowledge building, but the current research lacks a joint quantified evaluation method that combines these two aspects. Objectives: Based on the existing framework, we proposed a joint evaluation method for regulated learning and cognitive quality in collaborative knowledge building, and further extracted the evaluation indicators. Methods: This study involved 74 learners enrolled in a course named 'the Application of Modern Educational Technology' as the subject of study, and made a case analysis with this method. Results and Conclusions: First, the indicators of this joint evaluation method could complement the indicators of traditional frequency statistics methods and facilitate an analysis of regulated learning and cognitive quality in collaborative knowledge building. Second, the group with a higher proportion of high-level cognitive quality and socially shared regulation in collaborative knowledge building achieved better final scores. Finally, four types of groups were obtained through clustering: excellent, risky, mixed group, and highly collaborative group. This study introduced a joint evaluation method for regulated learning and cognitive quality in collaborative knowledge building and provides suggestions for future research.

Background: Identifying the diagnosis as well as prognosis for patients presented with community-acquired pneumonia (CAP) remains challenging. We aimed to identify the role of lysophosphatidylcholine acyl-transferase (LPCAT) for CAP along with assessing this protein's effectiveness as a biomarker for severity of disease and mortality. Methods: Prospective multicenter research study was carried out among hospitalized patients. A total of 299 CAP patients (including 97 severe CAP patients [SCAP]) and 20 healthy controls (HC) were included. A quantitative enzyme-linked immunosorbent test kit was employed for detecting the LPCAT level in plasma. We developed a deep-learning-based binary classification (SCAP or non-severe CAP [NSCAP]) model to process LPCAT levels and other laboratory test results. Results: The level of LPCAT in patients with SCAP and death outcome was significantly higher than that in other patients. LPCAT showed the highest predictive value for SCAP. LPCAT was able to predict 30-day mortality among CAP patients, combining LPCAT values with PSI scores or CURB-65 further enhance mortality prediction accuracy. Conclusion: The on admission level of LPCAT found significantly raised among SCAP patients and strongly predicted SCAP patients but with no correlation to etiology. Combining the LPCAT value with CURB-65 or PSI improved the 30-day mortality forecast significantly. Trial registration: NCT03093220 Registered on March 28th, 2017. [ABSTRACT FROM AUTHOR]