To gain an in-depth understanding of the clinical application of Rehmanniae Radix during the Qing Dynasty and to clarify its specifications and corresponding therapeutic effects， this study took Rehmanniae Radix in the prescriptions documented in Research on Medical Cases of the Qing Imperial Court as the research subject. According to historical medical literature， a comprehensive investigation was conducted on the specifications， therapeutic efficacy， frequency of use， dosage， and seasonal patterns of Rehmanniae Radix employed by imperial physicians. The findings revealed that Rehmanniae Radix in the medical cases of the Qing court was primarily classified into three categories： Xiaoshengdi， Zhongshengdi， and Dashengdi. Xiaoshengdi was also referred to as Xishengdi or Cishengdi， all denoting dried Rehmanniae Radix. The term Xishengdi was inconsistently defined in the literature. It should refer to the slender variant of dried Rehmanniae Radix and was utilized as a specific specification in the medical cases of the Qing court. In contrast， the wild fresh roots of Rehmanniae Radix， described as "as slender as fingers"， were commonly documented as fresh Rehmanniae Radix in these medical cases. There were variations in Rehmanniae Radix size and grading between historical and contemporary standards. Furthermore， therapeutic differences were observed among Rehmanniae Radix specifications in the medical cases of the Qing court. Xiaoshengdi and Zhongshengdi exhibited slightly stronger blood-cooling and heat-clearing effects while maintaining a non-cloying Yin-nourishing property. In contrast， Dashengdi demonstrated a greater emphasis on Yin supplementation with relatively milder heat-clearing activity. In the medical cases of the Qing court， the dosage of Rehmanniae Radix in different specifications was usually 11.2-18.7 g per dose， typically administered twice daily. Rehmanniae Radix in different specifications exhibits variations in efficacy， which can provide evidence-based insights for precise clinical application.

To gain an in-depth understanding of the clinical application of Rehmanniae Radix during the Qing Dynasty and to clarify its specifications and corresponding therapeutic effects， this study took Rehmanniae Radix in the prescriptions documented in Research on Medical Cases of the Qing Imperial Court as the research subject. According to historical medical literature， a comprehensive investigation was conducted on the specifications， therapeutic efficacy， frequency of use， dosage， and seasonal patterns of Rehmanniae Radix employed by imperial physicians. The findings revealed that Rehmanniae Radix in the medical cases of the Qing court was primarily classified into three categories： Xiaoshengdi， Zhongshengdi， and Dashengdi. Xiaoshengdi was also referred to as Xishengdi or Cishengdi， all denoting dried Rehmanniae Radix. The term Xishengdi was inconsistently defined in the literature. It should refer to the slender variant of dried Rehmanniae Radix and was utilized as a specific specification in the medical cases of the Qing court. In contrast， the wild fresh roots of Rehmanniae Radix， described as "as slender as fingers"， were commonly documented as fresh Rehmanniae Radix in these medical cases. There were variations in Rehmanniae Radix size and grading between historical and contemporary standards. Furthermore， therapeutic differences were observed among Rehmanniae Radix specifications in the medical cases of the Qing court. Xiaoshengdi and Zhongshengdi exhibited slightly stronger blood-cooling and heat-clearing effects while maintaining a non-cloying Yin-nourishing property. In contrast， Dashengdi demonstrated a greater emphasis on Yin supplementation with relatively milder heat-clearing activity. In the medical cases of the Qing court， the dosage of Rehmanniae Radix in different specifications was usually 11.2-18.7 g per dose， typically administered twice daily. Rehmanniae Radix in different specifications exhibits variations in efficacy， which can provide evidence-based insights for precise clinical application.

Over the past two decades, genome-wide association study(GWAS) has identified numerous genetic variants and loci associated with heritable diseases. With the gradual maturation and saturation of GWAS methodologies, transcriptome-wide association study(TWAS) offers a novel perspective by linkinggenetic phenotypes to gene expression levels. By integrating TWAS with other multi-omics analyses, researchers can gain a deeper understanding of heritable diseases. This article provides an overview of recent groundbreaking and representative TWAS methods and tools, analyzes their strengths and limitations, and discusses future trends in TWAS development.

Doxorubicin (DOX)-induced cardiotoxicity and sepsis-induced myocardial injury (SIMI) represent significant clinical challenges in patients undergoing chemotherapy, sharing a common pathological basis of oxidative stress and mitochondrial dysfunction. Ferroptosis, an iron-dependent form of regulated cell death driven by lipid peroxidation, has recently been shown to play a critical role in DOX-induced cardiotoxicity and lipopolysaccharide (LPS)-induced SIMI. This article systematically reviews the mechanisms underlying myocardial injury caused by DOX and sepsis, identifying ferroptosis as a central common pathway. DOX triggers a burst of reactive oxygen species within mitochondria and inhibits glutathione peroxidase 4 (GPX4) activity through redox cycling of its quinone group and high-affinity accumulation in mitochondrial cardiolipin. LPS, by activating pattern recognition receptors and related inflammatory signaling pathways, provokes a cytokine storm and mitochondrial dysfunction. Both can disrupt the core regulatory axis of cysteine-glutathione (GSH)-GPX4, synergistically promoting ferroptosis in cardiomyocytes. Moreover, epigenetic regulation plays a key role in DOX- and LPS-induced cardiomyocyte ferroptosis and may serve as a promising therapeutic target. A deeper understanding of the ferroptosis mechanism and its epigenetic regulatory network in the synergistic injury induced by DOX and sepsis is of great importance for developing novel strategies to mitigate chemotherapy-related cardiotoxicity and improve outcomes in cancer patients with concurrent infections.

To develop and validate a model for predicting intensive care unit (ICU) mortality risk in patients with malignant tumors complicated by acute respiratory failure (ARF) based on an explainable machine learning framework.

ObjectiveTo investigate the effects of Tianma Goutengyin on the tumor necrosis factor-α （TNF-α）/signal transducer and activator of transcription 3 （STAT3）/α1-antichymotrypsin C-terminal tail fragment （α1ACT） signaling pathway and A1-type astrocytes in a rat model of vascular dementia. MethodsSeventy-two male Sprague-Dawley rats were randomly divided into six groups （n=12 per group）： Sham-operated group， model group， Tianma Goutengyin high-， medium-， and low-dose groups （5.13， 10.26， and 20.52 g·kg^-1）， and a nimodipine group （8.1 mg·kg^-1）. The vascular dementia model was established by permanent bilateral common carotid artery occlusion， followed by 4 weeks of intervention. Learning and memory ability were evaluated using the novel object recognition test， and behavioral performance was assessed using the forced swimming test. Levels of interleukin-6 （IL-6） and C-C motif chemokine ligand 2 （CCL2） in hippocampal tissue were measured by enzyme-linked immunosorbent assay （ELISA）. Hippocampal neuronal morphology was observed by Nissl staining， and apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling （TUNEL）. Immunohistochemistry was used to detect positive expression of brain-derived neurotrophic factor （BDNF）， glial fibrillary acidic protein （GFAP）， and myelin basic protein （MBP）. Western blot analysis was performed to measure the protein expression levels of TNF-α， TNF receptor 1 （TNFR1）， phosphorylated STAT3 （p-STAT3）， α1ACT， IL-6， complement component 3 （C3）， BDNF， S100 calcium-binding protein A10 （S100A10）， and GFAP in hippocampal tissue. ResultsCompared with the sham-operated group， the model group showed a significantly reduced relative recognition index in the novel object recognition test （P<0.01）， prolonged immobility time and increased immobility frequency in the forced swimming test （P<0.01）. Hippocampal IL-6 and CCL2 levels were significantly increased （P<0.01）. Nissl staining revealed a marked reduction in neuronal number and loss of Nissl bodies （P<0.01）. MBP-positive expression was significantly decreased （P<0.01）， apoptosis was significantly increased （P<0.01）， BDNF-positive expression was significantly reduced （P<0.05）， and GFAP-positive expression was significantly increased （P<0.01）. In addition， the protein expression levels of TNF-α， TNFR1， p-STAT3， α1ACT， IL-6， and C3 were significantly elevated （P<0.01）， while BDNF and S100A10 expression levels were significantly decreased （P<0.01）. Compared with the model group， all Tianma Gouteng yin dose groups exhibited a significant increase in the relative recognition index （P<0.05）， shortened immobility time and reduced immobility frequency （P<0.05， P<0.01）. IL-6 and CCL2 levels were significantly decreased （P<0.01）， neuronal number was significantly increased （P<0.05， P<0.01）， and MBP-positive expression was significantly enhanced （P<0.01）. Apoptosis was significantly reduced （P<0.01）， BDNF-positive expression was significantly increased （P<0.05）， and GFAP-positive expression was significantly decreased （P<0.01）. Moreover， the protein expression levels of TNF-α， TNFR1， p-STAT3， α1ACT， IL-6， and C3 were significantly decreased （P<0.01）， while BDNF and S100A10 protein expression levels were significantly increased （P<0.01）. ConclusionTianma Goutengyin may inhibit A1-type astrocyte activation in rats with vascular dementia through the TNF-α/STAT3/α1ACT signaling pathway， thereby reducing neuronal apoptosis and improving learning and memory function.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Objective To summarize the clinical efficacy of modified Morrow surgery in the treatment of hypertrophic obstructive cardiomyopathy. Methods A retrospective analysis was conducted on the clinical data of patients with hypertrophic obstructive cardiomyopathy treated with modified Morrow surgery at Zhongshan Hospital Affiliated to Fudan University from 2020 to 2023. Results A total of 318 patients were enrolled, including 156 males and 162 females, with an average age of (55.6±13.1) years. Preoperative echocardiography showed a mean interventricular septal thickness of (18.1±3.8) mm, peak left ventricular outflow tract pressure difference of (86.4±24.9) mm Hg. The surgery time was (162.3±51.0) min, extracorporeal circulation time was (80.9±31.0) min, and aortic occlusion time was (44.8±20.8) min. After the surgery, transesophageal echocardiography showed that the interventricular septal thickness was (11.0±1.8) mm and left ventricular outflow tract peak pressure difference was (9.4±5.1) mm Hg. The incidence rate of postoperative complete left bundle branch block was 45.3%, Ⅲ° atrioventricular block was 3.8%, and postoperative newly developed atrial fibrillation was 3.1%. The postoperative hospital stay was (6.6±4.9) days, and one perioperative death occurred, with a mortality rate of 0.3%. The follow-up time was (10.3±9.4) months, during which the transthoracic echocardiography revealed a ventricular septal thickness of (12.9±2.9) mm and a peak left ventricular outflow tract pressure difference of (13.9±10.0) mm Hg. Conclusion The modified Morrow procedure for the treatment of hypertrophic obstructive cardiomyopathy is safe and effective, with good results in the short and medium term.

Objective: To explore the network structure of middle school students basic psychological needs and psychological behavioral problems, and identify the core nodes within the network, as well as examine demographic subgroup differences, so as to provide support for targeted mental health interventions for adolescents. Methods: In September and October of 2023, a total of 2 000 junior and senior high school students were selected with multistage cluster random sampling from 8 schools in Jiaojiang District and Tiantai County, Taizhou City. An online self administered questionnaire was used to assess emotional and behavioral problems, perceived autonomy, self awareness, loneliness, and social support. The instruments included the Strengths and Difficulties Questionnaire (SDQ), Perceived Choice and Awareness of Self Scale (PCASS), Mental Health Literacy Questionnaire (MHLQ), University of California,Los Angeles Loneliness Scale (UCLA-LS), and the Multidimensional Scale of Perceived Social Support (MSPSS). A network analysis approach was employed to construct a network representing adolescents basic psychological needs and psychological behavioral problems, focusing on centrality measures and demographic subgroup differences. Results: A total of 418 students (20.9%) reported abnormal emotional and behavioral problems. Perceived autonomy and competence were negatively correlated with emotional problems (weights: 0.12, 0.14) and hyperactivity (weights: 0.10, 0.16). Social support showed negative correlation with peer relationship issues, hyperactivity, and conduct problems (weights: 0.16, 0.13, 0.10). Loneliness was positively correlated with emotional symptoms and peer relationship problems (weights: 0.28, 0.18). In the overall network, perceived relationships (social support and loneliness), emotional symptoms, and hyperactivity emerged as central nodes. Significant differences in network structure were observed between gender subgroups ( P =0.02). Girls internalizing issues were more influenced by loneliness and perceived autonomy frustration, while social support exhibited higher centrality in boys. Conclusions Perceived relationships, emotional problems, and hyperactivity are key nodes in the network of adolescents basic psychological needs and psychological behavioral problems. Loneliness demonstrates a prominent influence within the network, and the overall network exhibits gender differences.