In this paper， by referring to ancient and modern literature， the textual research of Inulae Flos has been conducted to clarify the name， origin， production area， quality evaluation， harvesting， processing and others， so as to provide reference and basis for the development and utilization of famous classical formulas containing this herb. After textual research， it could be verified that the medicinal use of Inulae Flos was first recorded in Shennong Bencaojing of the Han dynasty. In successive dynasties， Xuanfuhua has been taken as the official name， and it also has other alternative names such as Jinfeicao， Daogeng and Jinqianhua. The period before the Song and Yuan dynasties， the main origin of Inulae Flos was the Asteraceae plant Inula japonica， and from the Ming and Qing dynasties to the present， I. japonica and I. britannica are the primary source. In addition to the dominant basal species， there are also regional species such as I. linariifolia， I. helianthus-aquatili， and I. hupehensis. The earliest recorded production areas in ancient times were Henan， Hubei and other places， and the literature records that it has been distributed throughout the country since modern times. The medicinal part is its flower， the harvesting and processing method recorded in the past dynasties is mainly harvested in the fifth and ninth lunar months， and dried in the sun， and the modern harvesting is mostly harvested in summer and autumn when the flowers bloom， in order to remove impurities， dry in the shade or dry in the sun. In addition， the roots， whole herbs and aerial parts are used as medicinal materials. In ancient times， there were no records about the quality of Inulae Flos， and in modern times， it is generally believed that the quality of complete flower structure， small receptacles， large blooms， yellow petals， long filaments， many fluffs， no fragments， and no branches is better. Ancient processing methods primarily involved cleaning， steaming， and sun-drying， supplemented by techniques such as boiling， roasting， burning， simmering， stir-frying， and honey-processing. Modern processing focuses mainly on cleaning the stems and leaves before use. Regarding the medicinal properties， ancient texts describe it as salty and sweet in taste， slightly warm in nature， and mildly toxic. Modern studies characterize it as bitter， pungent， and salty in taste， with a slightly warm nature. Its therapeutic effects remain consistent across eras， including descending Qi， resolving phlegm， promoting diuresis， and stopping vomiting. Based on the research results， it is recommended that when developing famous classical formulas containing Inulae Flos， either I. japonica or I. britannica should be used as the medicinal source. Processing methods should follow formula requirements， where no processing instructions are specified， the raw products may be used after cleaning.

In this paper， by referring to ancient and modern literature， the textual research of Inulae Flos has been conducted to clarify the name， origin， production area， quality evaluation， harvesting， processing and others， so as to provide reference and basis for the development and utilization of famous classical formulas containing this herb. After textual research， it could be verified that the medicinal use of Inulae Flos was first recorded in Shennong Bencaojing of the Han dynasty. In successive dynasties， Xuanfuhua has been taken as the official name， and it also has other alternative names such as Jinfeicao， Daogeng and Jinqianhua. The period before the Song and Yuan dynasties， the main origin of Inulae Flos was the Asteraceae plant Inula japonica， and from the Ming and Qing dynasties to the present， I. japonica and I. britannica are the primary source. In addition to the dominant basal species， there are also regional species such as I. linariifolia， I. helianthus-aquatili， and I. hupehensis. The earliest recorded production areas in ancient times were Henan， Hubei and other places， and the literature records that it has been distributed throughout the country since modern times. The medicinal part is its flower， the harvesting and processing method recorded in the past dynasties is mainly harvested in the fifth and ninth lunar months， and dried in the sun， and the modern harvesting is mostly harvested in summer and autumn when the flowers bloom， in order to remove impurities， dry in the shade or dry in the sun. In addition， the roots， whole herbs and aerial parts are used as medicinal materials. In ancient times， there were no records about the quality of Inulae Flos， and in modern times， it is generally believed that the quality of complete flower structure， small receptacles， large blooms， yellow petals， long filaments， many fluffs， no fragments， and no branches is better. Ancient processing methods primarily involved cleaning， steaming， and sun-drying， supplemented by techniques such as boiling， roasting， burning， simmering， stir-frying， and honey-processing. Modern processing focuses mainly on cleaning the stems and leaves before use. Regarding the medicinal properties， ancient texts describe it as salty and sweet in taste， slightly warm in nature， and mildly toxic. Modern studies characterize it as bitter， pungent， and salty in taste， with a slightly warm nature. Its therapeutic effects remain consistent across eras， including descending Qi， resolving phlegm， promoting diuresis， and stopping vomiting. Based on the research results， it is recommended that when developing famous classical formulas containing Inulae Flos， either I. japonica or I. britannica should be used as the medicinal source. Processing methods should follow formula requirements， where no processing instructions are specified， the raw products may be used after cleaning.

Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

BackgroundPatients with depressive disorder often exhibit impaired decision-making functions. However， the relationship between decision-making abilities and depressive and anxiety symptoms in these patients remains unclear. ObjectiveTo explore the characteristics of decision-making behavior in patients with depressive disorder， and to analyze its relationship with clinical symptoms. MethodsA total of 48 patients diagnosed with depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders， fourth edition （DSM-IV） were recruited from the Department of Psychosomatic Medicine of the Affiliated Hospital of Southwest Medical University from October 2020 to May 2023. Concurrently， 52 healthy individuals matched for age and gender were recruited from Luzhou as the control group. Beck Depression Inventory （BDI） and Beck Anxiety Inventory （BAI） were used for assessment， and decision-making behavior was evaluated using Probabilistic Reversal Learning （PRL） task. Indicators assessed included the number of trials to criterion， perseverative errors， win-stay rate and lose-shift rate. Spearman correlation analysis was used to assess the correlation between BDI and BAI scores and PRL task indicators. ResultsThe depression group showed a significantly higher lose-shift rate compared with the control group （t=3.684， P<0.01）. There were no statistically significant differences between two groups in trials to criterion， perseverative errors and win-stay rate （t=0.329， 0.132， 0.609， P>0.05）. In depression group， BDI and BAI scores were positively correlated with the win-stay rate（r=0.450， 0.398， P<0.01）. ConclusionPatients with depressive disorder are more likely to change their decision-making strategies following negative outcomes. Furthermore， the severity of depressive and anxiety symptoms is associated with a greater propensity to maintain existing decisions after receiving positive feedback. ［Funded by 2019 Joint Project of Luzhou Science and Technology Bureau-Southwest Medical University （number， 2019LZXNYDJ39］

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.