ObjectiveTo systematically evaluate the content differences of 4 components in Leonuri Herba granules， reveal the quality fluctuation patterns of products from the same and different manufacturers， providing scientific basis for the optimization of production process and quality control. MethodsHigh performance liquid chromatography-diode array detector-charged aerosol detector（HPLC-DAD-CAD） was employed to determine the contents of 4 components（syringic acid， leonurine hydrochloride， ferulic acid， and stachydrine hydrochloride） in samples from 19 manufacturers（53 batches， 159 boxes）. Additionally， fingerprint profiles were constructed， and the fingerprint dissimilarity（P_S） and relative standard deviation（RSD） of different samples from the same manufacturer were calculated. A principal component analysis（PCA） model was established with P_S and the RSD values of the 4 components as variables to classify the manufacturers. Finally， samples from 5 manufacturers（M1-M5） covering three consistency groups were selected to calculate three quality consistency parameters， namely intra-batch consistency（P_A）， inter-batch consistency（P_B）， and P_S. Then， PCA was performed with P_A， P_B， and P_S of these 5 manufacturers as variables. ResultsThe average total content of the 4 index components per bag across the 19 manufacturers ranged from 41.10 mg to 97.54 mg. Among them， the content of stachydrine hydrochloride（a pharmacopoeial quality control component） was 32.46-72.70 mg per bag， all meeting the requirements of the 2025 edition of the Pharmacopoeia of the People's Republic of China， with RSD of 1.7%-17.1%. The content ranges of the other 3 components were as follows：syringic acid of 1.43-41.92 mg per bag， leonurine hydrochloride of 0.67-11.85 mg per bag， and ferulic acid of 0.11-3.81 mg per bag. Notably， leonurine hydrochloride exhibited the most significant content fluctuation among samples from the same manufacturer（RSD of 4.8%-59.2%）. PCA results showed that the 19 manufacturers could be classified into 3 categories. Samples from 8 manufacturers（M2， M6， M7， M8， M10， M15， M17， M18） demonstrated relatively high consistency， five manufacturers（M3， M9， M12， M13， M14） showed moderate consistency， six manufacturers（M1， M4， M5， M11， M16， M19） exhibited low consistency. The two methods yielded consistent classification results for the 5 representative manufacturers， verifying the reliability of the proposed method. Among these， manufacturer M2 showed the best quality consistency and the highest total content of indicator components among M1-M5. ConclusionThe HPLC-DAD-CAD multi-detector hyphenation technology established in this study enables the accurate detection of 4 components in Leonuri Herba granules. Significant differences in the total content of these four components are observed among products from 19 manufacturers. The application of 2 consistency evaluation methods combined with PCA can effectively classify their consistency into 3 categories， and the classification results of the 2 methods are highly consistent. This study provides scientific basis for the process optimization and quality standard improvement of Leonuri Herba granules.

ObjectiveTo systematically evaluate the content differences of 4 components in Leonuri Herba granules， reveal the quality fluctuation patterns of products from the same and different manufacturers， providing scientific basis for the optimization of production process and quality control. MethodsHigh performance liquid chromatography-diode array detector-charged aerosol detector（HPLC-DAD-CAD） was employed to determine the contents of 4 components（syringic acid， leonurine hydrochloride， ferulic acid， and stachydrine hydrochloride） in samples from 19 manufacturers（53 batches， 159 boxes）. Additionally， fingerprint profiles were constructed， and the fingerprint dissimilarity（P_S） and relative standard deviation（RSD） of different samples from the same manufacturer were calculated. A principal component analysis（PCA） model was established with P_S and the RSD values of the 4 components as variables to classify the manufacturers. Finally， samples from 5 manufacturers（M1-M5） covering three consistency groups were selected to calculate three quality consistency parameters， namely intra-batch consistency（P_A）， inter-batch consistency（P_B）， and P_S. Then， PCA was performed with P_A， P_B， and P_S of these 5 manufacturers as variables. ResultsThe average total content of the 4 index components per bag across the 19 manufacturers ranged from 41.10 mg to 97.54 mg. Among them， the content of stachydrine hydrochloride（a pharmacopoeial quality control component） was 32.46-72.70 mg per bag， all meeting the requirements of the 2025 edition of the Pharmacopoeia of the People's Republic of China， with RSD of 1.7%-17.1%. The content ranges of the other 3 components were as follows：syringic acid of 1.43-41.92 mg per bag， leonurine hydrochloride of 0.67-11.85 mg per bag， and ferulic acid of 0.11-3.81 mg per bag. Notably， leonurine hydrochloride exhibited the most significant content fluctuation among samples from the same manufacturer（RSD of 4.8%-59.2%）. PCA results showed that the 19 manufacturers could be classified into 3 categories. Samples from 8 manufacturers（M2， M6， M7， M8， M10， M15， M17， M18） demonstrated relatively high consistency， five manufacturers（M3， M9， M12， M13， M14） showed moderate consistency， six manufacturers（M1， M4， M5， M11， M16， M19） exhibited low consistency. The two methods yielded consistent classification results for the 5 representative manufacturers， verifying the reliability of the proposed method. Among these， manufacturer M2 showed the best quality consistency and the highest total content of indicator components among M1-M5. ConclusionThe HPLC-DAD-CAD multi-detector hyphenation technology established in this study enables the accurate detection of 4 components in Leonuri Herba granules. Significant differences in the total content of these four components are observed among products from 19 manufacturers. The application of 2 consistency evaluation methods combined with PCA can effectively classify their consistency into 3 categories， and the classification results of the 2 methods are highly consistent. This study provides scientific basis for the process optimization and quality standard improvement of Leonuri Herba granules.

Objective:To evaluate the clinical utility of dual-layer detector CT integrated with virtual monoenergetic imaging (VMI) and an orthopedic metal artifact reduction (O-MAR) algorithm in improving the image quality of patients after lumbar pedicle screw fixation surgery, and to analyze its impact on different types of artifacts and image quality of different tissues.Methods:The study was a prospective study, The study enrolled patients who underwent lumbar pedicle screw fixation at West China Hospital of Sichuan University between March and September 2024. All patients underwent lumbar CT scans using a dual-layer detector system, and four image sets were reconstructed. CLumbar routine scans were performed using dual-layer detector CT, and four image sets were reconstructed:onventional images (CI non-O-MAR), conventional images with O-MAR (CI O-MAR), virtual monoenergetic images (VMI non-O-MAR), and VMI with O-MAR (VMI O-MAR). Objective metrics including artifact index (AI), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were quantified, alongside subjective image quality assessment. One-way ANOVA or Friedman test were used to compare the objective evaluation indicators of image quality between VMI non-O-MAR and VMI O-MAR at different energy levels. Paired t-test or Wilcoxon signed-rank test was used for CI non-O-MAR/VMI non-O-MAR versus CI O-MAR/VMI O-MAR comparisons. Results:A total of 30 patients were included, and all underwent internal fixation with titanium alloy pedicle screws. Objective analysis revealed that in both high-and low-density artifact regions, the AI values of the VMI O-MAR group decreased with the increase of energy levels, and were significantly lower than those of the corresponding VMI non-O-MAR group, with a statistically significant difference (all P<0.001). When the energy level≥140 keV, the AI value of the VMI O-MAR group was simultaneously lower than that of the CI non-O-MAR group and the CI O-MAR group, with statistically significant differences (all P<0.05). The SNR and CNR on the vertebral bodies in the VMI non-O-MAR group and the VMI O-MAR group showed a decreasing trend with increasing energy levels, and were always lower than those in the CI group at high energy levels (100-180 keV) (all P<0.05). At high energy levels (100-180 keV), the SNR of VMI O-MAR in the intervertebral disc and intraspinal tissues was higher than that of the VMI non-O-MAR group, with statistically significant differences (all P<0.05). Compared to other groups, subjective analysis indicated that the 140 keV VMI combined with O-MAR group received the highest image quality scores ( P<0.05). Conclusions:The combined application of VMI and O-MAR technology effectively reduces metal artifacts in post-lumbar fixation CT images. The 140 keV VMI with O-MAR reconstruction provides superior image quality and enhances diagnostic confidence.

ObjectiveTo study the effect of Taikong Yangxin Pills on the metabolism of simulated weightless rats based on metabolomics and discuss the metabolism mechanism. MethodsIn the simulated space capsule environment on the ground， the rat model of simulated weightlessness was established by the tail suspension method. Rats were randomly grouped as follows： out-of-capsule control， in-capsule control， model， and high （3.0 g·kg^-1） and low （1.5 g·kg^-1） doses of Taikong Yangxin Pills， and they were administrated with corresponding drugs by gavage for 28 days. The serum levels of endogenous metabolites in rats were determined by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry （UPLC-Q-TOF/MS）. The obtained data were processed by principal component analysis （PCA） and orthogonal partial least squares-discriminant analysis （OPLS-DA） to screen for differential metabolites and potential biomarkers. MetaboAnalyst 5.0 was used for pathway enrichment analysis to explain the metabolic regulation mechanism of the drug. ResultsCompared with the out-of-capsule control group， the in-capsule control group showed elevated levels of thirteen metabolites， including 14-hydroxyhexadecanoic acid， linoleic acid， and α-linolenic acid （P<0.05）， which suggested that the space capsule environment mainly affected the metabolism of α-linolenic acid and linoleic acid in the rats. Compared with the in-capsule control group， the model group showed lowered levels of fourteen metabolites， including 4-imidazolone-5-propionic acid， isocitric acid/citric acid， and L-tyrosine （P<0.05）， which were recovered after the treatment with Taikong Yangxin pills （P<0.05）. The pathway enrichment analysis revealed that weightlessness induced by tail suspension and drug intervention mainly involved the phenylalanine， tyrosine， and tryptophan biosynthesis， tyrosine metabolism， histidine metabolism， and citric acid cycle. ConclusionThe simulated space capsule environment and simulated weightlessness induced by tail suspension can both affect the metabolism level of rats. Taikong Yangxin pills can ameliorate the metabolic abnormality in the rat model of weightlessness by regulating various amino acids and energy metabolism-related pathways.

ObjectiveTo establish the fingerprints of 15 batches of Hengzhi Kechuan capsules， to quantitatively analyze 10 index components， and to evaluate the quality uniformity of samples from different batches. MethodsThe fingerprints and quantitative analysis of Hengzhi Kechuan capsules were established by a combination method of high performance liquid chromatography coupled with diode array detector and charged aerosol detector（HPLC-DAD-CAD）， adenosine， guanosine， vanillic acid， safflomin A， agarotetrol， naringin， hesperidin， militarine， ginsenoside Rb₁， and glycyrrhizic acid were selected as quality attribute indexes. A total of 15 batches of Hengzhi Kechuan capsules from 2022 to 2024（3 boxes per batch） were qualitatively and quantitatively analyzed， and the quality uniformity level of the manufacturers was characterized by parameters of intra-batch consistency（P_A） and inter-batch consistency（P_B）. The homogeneity and difference of quality attribute indexes of samples from different years were analyzed by heatmap clustering analysis. ResultsHPLC fingerprints and quantitative method of Hengzhi Kechuan capsules were established， and the methods could be used for qualitative and quantitative analysis of this preparation， which was found to be stable and reliable by method validation. The similarity of fingerprints of 15 batches of samples was 0.887-0.975， a total of 13 common peaks were calibrated， and 10 common peaks were designated， all of which were quality attribute index components. The results of quantitative analysis showed that the contents of the above 10 ingredients in the samples were 0.038-0.078， 0.115-0.251， 0.007-0.018， 0.291-0.673， 0.122-0.257， 0.887-1.905， 1.841-3.364， 1.412-2.450， 2.207-3.112， 0.650-1.161， respectively. And the contents of ginsenoside Rb₁ and glycyrrhizic acid met the limit requirements in the 2020 edition of Chinese Pharmacopoeia. For the samples from 15 batches， the P_A values of the 10 index components were all <10%， indicating good intra-batch homogeneity， and the P_B values ranged from 33.86% to 92.97%， suggesting that the inter-batch homogeneity was poor. Heatmap clustering analysis showed that the samples from different years were clustered into separate categories， and adenosine， guanosine， safflomin A， naringin， hesperidin and agarotetrol were the main differential components. ConclusionThe intra-annual quality uniformity of Hengzhi Kechuan capsules is good and the inter-annual quality uniformity is insufficient， which may be related to the quality difference of Pinellinae Rhizoma Praeparatum， Carthami Flos， Citri Sarcodactylis Fructus， Citri Reticulatae Pericarpium， Aquilariae Lignum Resinatum， Citri Fructus， etc. In this study， the fingerprint and multi-indicator determination method of Hengzhi Kechuan capsules was established， which can be used for more accurate and efficient quality control and standardization enhancement.

Ventilator-induced lung injury(VILI)is a form of lung injury caused by inappropriate ventilator parameter settings or pre-existing lung pathologies during mechanical ventilation.The pathogenesis of VILI is complex,primarily involving barotrauma,volutrauma,atelectrauma,and biotrauma.To prevent VILI,clinical practice advocates protective lung ventilation strategies and personalized positive end-expiratory pressure(PEEP)settings.Early identification and precise assessment are critical for improving patient outcomes.The rapid advancement of imaging technologies has provided multidimensional perspectives for dynamic monitoring of VILI.This review summarizes the imaging principles,clinical applications in the context of VILI management,and limitations of various imaging modalities,including lung ultrasound(LUS),computed tomography(CT),electrical impedance tomography(EIT),and magnetic resonance imaging(MRI).By offering comprehensive diagnostic information,this review aims to provide a theoretical foundation for the precise assessment of VILI and the optimization of ventilatory support strategies.

Objective:To evaluate the clinical utility of dual-layer detector CT integrated with virtual monoenergetic imaging (VMI) and an orthopedic metal artifact reduction (O-MAR) algorithm in improving the image quality of patients after lumbar pedicle screw fixation surgery, and to analyze its impact on different types of artifacts and image quality of different tissues.Methods:The study was a prospective study, The study enrolled patients who underwent lumbar pedicle screw fixation at West China Hospital of Sichuan University between March and September 2024. All patients underwent lumbar CT scans using a dual-layer detector system, and four image sets were reconstructed. CLumbar routine scans were performed using dual-layer detector CT, and four image sets were reconstructed:onventional images (CI non-O-MAR), conventional images with O-MAR (CI O-MAR), virtual monoenergetic images (VMI non-O-MAR), and VMI with O-MAR (VMI O-MAR). Objective metrics including artifact index (AI), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were quantified, alongside subjective image quality assessment. One-way ANOVA or Friedman test were used to compare the objective evaluation indicators of image quality between VMI non-O-MAR and VMI O-MAR at different energy levels. Paired t-test or Wilcoxon signed-rank test was used for CI non-O-MAR/VMI non-O-MAR versus CI O-MAR/VMI O-MAR comparisons. Results:A total of 30 patients were included, and all underwent internal fixation with titanium alloy pedicle screws. Objective analysis revealed that in both high-and low-density artifact regions, the AI values of the VMI O-MAR group decreased with the increase of energy levels, and were significantly lower than those of the corresponding VMI non-O-MAR group, with a statistically significant difference (all P<0.001). When the energy level≥140 keV, the AI value of the VMI O-MAR group was simultaneously lower than that of the CI non-O-MAR group and the CI O-MAR group, with statistically significant differences (all P<0.05). The SNR and CNR on the vertebral bodies in the VMI non-O-MAR group and the VMI O-MAR group showed a decreasing trend with increasing energy levels, and were always lower than those in the CI group at high energy levels (100-180 keV) (all P<0.05). At high energy levels (100-180 keV), the SNR of VMI O-MAR in the intervertebral disc and intraspinal tissues was higher than that of the VMI non-O-MAR group, with statistically significant differences (all P<0.05). Compared to other groups, subjective analysis indicated that the 140 keV VMI combined with O-MAR group received the highest image quality scores ( P<0.05). Conclusions:The combined application of VMI and O-MAR technology effectively reduces metal artifacts in post-lumbar fixation CT images. The 140 keV VMI with O-MAR reconstruction provides superior image quality and enhances diagnostic confidence.

Ventilator-induced lung injury(VILI)is a form of lung injury caused by inappropriate ventilator parameter settings or pre-existing lung pathologies during mechanical ventilation.The pathogenesis of VILI is complex,primarily involving barotrauma,volutrauma,atelectrauma,and biotrauma.To prevent VILI,clinical practice advocates protective lung ventilation strategies and personalized positive end-expiratory pressure(PEEP)settings.Early identification and precise assessment are critical for improving patient outcomes.The rapid advancement of imaging technologies has provided multidimensional perspectives for dynamic monitoring of VILI.This review summarizes the imaging principles,clinical applications in the context of VILI management,and limitations of various imaging modalities,including lung ultrasound(LUS),computed tomography(CT),electrical impedance tomography(EIT),and magnetic resonance imaging(MRI).By offering comprehensive diagnostic information,this review aims to provide a theoretical foundation for the precise assessment of VILI and the optimization of ventilatory support strategies.

Objective To investigate the risk factors for secondary infection in patients with acute ischemic stroke(AIS)undergoing intravenous thrombolysis,and to construct a nomogram model.Methods A retrospective analysis was performed for the clinical data of 391 patients with AIS who underwent intravenous thrombolysis in Nanjing Drum Tower Hospital retrospectively from December 2016 to December 2021,and according to the presence of absence of secondary in-fection,they were divided into infection group with 75 patients and non-infection group with 316 patients.Results Age[odds ratio(OR)=1.049,95%confidence interval(CI)1.017-1.082],history of renal insufficiency(OR=3.76,95%CI 1.382-9.966),history of antihypertensive drugs(OR=0.298,95%CI 0.144-0.562),hemorrhagic transforma-tion after thrombolysis(OR=2.851,95%CI 1.05-7.36),white blood cell count(WBC)on admission(OR=1.17,95%CI 1.045-1.313),prothrombin time(PT)on admission(OR=1.585,95%CI 1.206-2.167),and dysphagia(OR=8.309,95%CI 4.091-17.269)were independent risk factors for secondary infection.The nomogram predictive model based on these risk factors had an area under the ROC curve of 0.867 and a cutoff value of 0.180,suggesting that the model had good discriminatory ability and calibration.According to the cutoff value of the nomogram,the patients were di-vided into high-risk and low-risk groups based on the risk of secondary infection,and the low-risk group had a significantly higher cumulative survival rate than the high-risk group(P<0.000 1).Conclusion Age,history of renal insufficiency,his-tory of antihypertensive drugs,hemorrhagic transformation after thrombolysis,WBC on admission,PT on admission,and dysphagia on admission are risk factors for secondary infection in AIS patients after intravenous thrombolysis,and the nomo-gram predictive model constructed based on the above risk factors has a good value in predicting secondary infection and 90-day survival.

Objective:To explore the influence of head nurse empowerment on nurses′ voice behavior and the mediating and moderating effects of nurses′ job crafting and proactive personality.Methods:A total of 805 nurses from the 4 grade A hospitals in Shandong province from February to March 2022 were selected by convenience sampling method, the Nurse Managers′ Empowering Behavioral Scale For Staff Nurses, Job Crafting Scale, Voice Behavior Scale and Proactive Personality Scale were used for cross-sectional survey. The mediating effect was analyzed by SPSS 26.0 and Process 3.4 macro.Results:The total score of nurses′ perception of head nurse empowerment was (4.01 ± 0.57) points, the total score of nurses′ job crafting was (4.19 ± 0.66) points, the total score of nurses′ voice behavior was (4.12 ± 0.62) points, and the total score of nurses′ proactive personality was (6.07 ± 0.90) points. Head nurse empowerment, nurse job crafting, voice behavior and proactive personality were positively correlated with each other ( r values were 0.483-0.824, all P<0.01). The mediating effect of job crafting was 0.541, accounting for 86.4% of the total effect; proactive personality had a positive moderating effect on the first half path of the mediation model ( ? R 2=0.163, P<0.01). Conclusions:Head nurse empowerment influenced voice behavior of nurses directly and indirectly through the mediating role of job crafting, proactive personality can moderate the effect of head nurse empowerment on nurse job crafting. It is suggested that the head nurse appropriately delegate power to the nurses and actively authorize them, identify nurses with high proactive personality, stimulate their job remodeling and voice behavior, and improve the quality of nursing work.