BACKGROUND: There is little literature describing the artificial intelligence (AI)-aided diagnosis of severe pneumonia (SP) subphenotypes and the association of the subphenotypes with the ventilatory treatment efficacy. The aim of our study is to illustrate whether clinical and biological heterogeneity, such as ventilation and gas-exchange, exists among patients with SP using chest computed tomography (CT)-based AI-aided latent class analysis (LCA). METHODS: This retrospective study included 413 patients hospitalized at Xinhua Hospital diagnosed with SP from June 1, 2015 to May 30, 2020. AI quantification results of chest CT and their combination with additional clinical variables were used to develop LCA models in an SP population. The optimal subphenotypes were determined though evaluating statistical indicators of all the LCA models, and clinical implications of them such as guiding ventilation strategies were further explored by statistical methods. RESULTS: The two-class LCA model based on AI quantification results of chest CT can describe the biological characteristics of the SP population well and hence yielded the two clinical subphenotypes. Patients with subphenotype-1 had milder infections ( P <0.001) than patients with subphenotype-2 and had lower 30-day ( P <0.001) and 90-day ( P <0.001) mortality, and lower in-hospital ( P = 0.001) and 2-year ( P <0.001) mortality. Patients with subphenotype-1 showed a better match between the percentage of non-infected lung volume (used to quantify ventilation) and oxygen saturation (used to reflect gas exchange), compared with patients with subphenotype-2. There were significant differences in the matching degree of lung ventilation and gas exchange between the two subphenotypes ( P <0.001). Compared with patients with subphenotype-2, those with subphenotype-1 showed a relatively better match between CT-based AI metrics of the non-infected region and oxygenation, and their clinical outcomes were effectively improved after receiving invasive ventilation treatment. CONCLUSIONS A two-class LCA model based on AI quantification results of chest CT in the SP population particularly revealed clinical heterogeneity of lung function. Identifying the degree of match between ventilation and gas-exchange may help guide decisions about assisted ventilation.
Humans ; Tomography, X-Ray Computed/methods* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Artificial Intelligence ; Aged ; Pneumonia/diagnosis* ; Latent Class Analysis ; Adult

ObjectiveTo investigate the anti-Alzheimer's disease （AD） effect of Dipsacus asper（DA） in the Caenorhabditis elegans model， and decipher the underlying mechanism via the peroxisome proliferator-activated receptor α （PPARα）/transcription factor EB （TFEB） pathway. MethodsFirst， transgenic AD C. elegans individuals were assigned into the blank control， model， positive control （WY14643， 20 µmol·L^-1）， and low-， medium-， and high-dose （100， 200， and 400 mg·L^-1， respectively） DA groups. The amyloid β-42 （Aβ₄₂） formation in the muscle cells， the paralysis time， and the deposition of amyloid β-protein （Aβ） in the head were detected. The lysosomal autophagy in the BV2 cell model was examined by Rluc-LC3wt/G120A. The expression levels of lysosomal autophagy-related proteins LC3Ⅱ， LC3I， LAMP2， and TFEB were detected by Western blot. Real-time quantitative polymerase chain reaction （Real-time PCR） was employed to determine the mRNA levels of autophagy-related genes beclin1 and Atg5 and lysosome-related genes LAMP2 and CLN2 downstream of PPARα/TFEB. A reporter gene assay was used to detect the transcriptional activities of PPARα and TFEB. Immunofluorescence was used to detect the fluorescence intensity of PPARα， and the active components of the ethanol extract of DA were identified by UPLC-MS. RCSB PDB， Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， and Autodock were used to analyze the binding between the active components and PPARα-ligand-binding domain （LBD）. ResultsCompared with the model group， the positive control group and 200 and 400 mg·L^-1 DA groups showed prolonged paralysis time （P<0.05）， and all the treatment groups showed decreased Aβ deposition in the head （P<0.01）. DA within the concentration range of 50-500 mg·L^-1 did not affect the viability of BV2 cells. In addition， DA enhanced the autophagy flux （P<0.05）， up-regulated the mRNA levels of beclin1， Atg5， LAMP2， and CLN2 （P<0.05， P<0.01）， promoted the nuclear translocation of TFEB （P<0.05）， increased LAMP2 expression and autophagy flux （P<0.05， P<0.01）， and enhanced the transcriptional activities of PPARα and TFEB （P<0.01）. The positive control group and 200 and 400 mg·L^-1 DA groups showed enhanced fluorescence intensity of PPARα in the BV2 nucleus （P<0.01）. UPLC-MS detected nine known compounds of DA， from which 8 active components of DA were screened out. The docking results suggested that a variety of components in DA could bind to PPARα-LBD and form stable hydrogen bonds. ConclusionDA may reduce the pathological changes in AD by regulating the PPARα-TFEB pathway.

Objective To explore the mediating effect of patient trust between outpatient appointment and medical expe-rience,and to provide academic reference for improving patients' medical experience.Methods Using 1 200 samples of ques-tionnaire survey conducted in the outpatient department of Tianjin First Central Hospital from December 2024 to March 2025,the correlation among outpatient appointment,medical experience and patient trust was analyzed,and the mediation effect model was constructed by using the Model 4 module in the SPSS 27.0 Process plug-in to test the mediation effect of patient trust.Results The study found that patients' trust plays a completely mediating role in the model(95％CI:0.044 6-0.180 5,P＜0.05),and outpatient appointment can improve patients' medical experience by improving patients' trust.Conclusion Outpatient appoint-ment can not only directly affect patients' medical experience,but also indirectly affect patients' medical experience through the intermediary trusted by patients.A perfect outpatient appointment system is helpful to guide patients to build trust in the hospital and promote the improvement of patients' medical experience.

Objective To explore the mediating effect of patient trust between outpatient appointment and medical expe-rience,and to provide academic reference for improving patients' medical experience.Methods Using 1 200 samples of ques-tionnaire survey conducted in the outpatient department of Tianjin First Central Hospital from December 2024 to March 2025,the correlation among outpatient appointment,medical experience and patient trust was analyzed,and the mediation effect model was constructed by using the Model 4 module in the SPSS 27.0 Process plug-in to test the mediation effect of patient trust.Results The study found that patients' trust plays a completely mediating role in the model(95％CI:0.044 6-0.180 5,P＜0.05),and outpatient appointment can improve patients' medical experience by improving patients' trust.Conclusion Outpatient appoint-ment can not only directly affect patients' medical experience,but also indirectly affect patients' medical experience through the intermediary trusted by patients.A perfect outpatient appointment system is helpful to guide patients to build trust in the hospital and promote the improvement of patients' medical experience.

OBJECTIVE To explore the effect mechanism of ethanol extract from Atractylodes macrocephala （EEAM） on microglial phagocytosis and degradation of amyloid β （Aβ） based on peroxisome proliferator-activated receptor γ （PPAR- γ） signaling pathway. METHODS Taking neuromicroglial cell BV2 as subjects， confocal microscopy was used to observe the effects of EEAM （0.3， 0.4， 0.5 mg/mL， similarly hereinafter） on phagocytosis and degradation of Aβ in microglia. Human embryonic kidney cell HEK293 was used to investigate the effects of EEAM on luciferase transcriptional activity of PPAR-γ. The effect of EEAM on nuclear translocation of PPAR-γ was investigated by immunofluorescence. Alzheimer’s disease BV2 cell model was induced by Aβ1-42， and quantitative polymerase chain reaction was used to investigate the effects of EEAM on mRNA expressions of PPAR-γ downstream target genes （Lxra， Lxrb， Abca1， Abcg1， Cd36， Sra and Apoe）. RESULTS The results of Aβ uptake experiment showed that after the intervention of medium and high doses of EEAM， fluorescence intensity of Aβ in BV2 cells increased significantly （P＜0.05）. The degradation experiment of Aβ showed that after the intervention of medium and high doses of EEAM， fluorescence intensity of Aβ in BV2 cells decreased significantly （P＜0.05）. After the intervention of different doses of EEAM， luciferase transcriptional activity of PPAR-γ in HEK293 cells increased significantly （P＜0.05）； fluorescence intensity of PPAR-γ in BV2 cells and nuclei （except for low-dose group） increased significantly （P＜0.05）. mRNA expressions of Lxra， Lxrb， Abca1， Abcg1， Cd36， Sra and Apoe in BV2 cells were increased significantly （P＜0.05）. CONCLUSIONS EEAM can promote the uptake and degradation of Aβ in microglia by activating PPAR-γ signaling pathway， thus improving Alzheimer’s disease.