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.

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.

Endometriosis （EMT） is a common disease with frequent occurrence and difficult to be cured in modern clinical practice of obstetrics and gynaecology. It is characterized by progressively worsening dysmenorrhoea， pelvic mass， and infertility. The incidence of EMT is growing and increasingly younger patients are diagnosed with this disease， which poses a serious threat to the reproductive and psychological health of women of childbearing age and adolescent females. However， the pathogenesis of EMT is still not completely clear， and the disease has a long course. Therefore， developing new therapies is an urgent clinical problem to be solved. Great progress has been achieved in the treatment of EMT with traditional Chinese medicine （TCM）， while the underlying mechanism remains in exploration. Programmed cell death （PCD） is a cell death mode mediated by a variety of bio-molecules with specific signaling cascades. The known PCD processes include apoptosis， pyroptosis， autophagy， ferroptosis， and cuproptosis， which all play a pivotal role in the development of EMT. Researchers have made achievements in the treatment of EMT with TCM， which regulates PCD via multiple pathways， routes， targets， and mechanisms. However， the progress in the regulation of PCD in the treatment of EMT with TCM remains to be reviewed. This paper reviews the research progress in the treatment of EMT with TCM from five PCD processes （apoptosis， pyroptosis， autophagy， ferroptosis， and cuproptosis）， with the aim of providing a theoretical basis for the clinical prevention and treatment of EMT.

Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

ObjectiveTo reveal the active substances and mechanisms of modified Qing'e formula （MQEF） in delaying skin photoaging by ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry （UPLC-Q-TOF-MS），network pharmacology， and cell experiments. MethodsUPLC-Q-TOF-MS and a literature review were employed to analyze the transdermally absorbed components in mice after the topical application of MQEF. The potential targets of MQEF in treating skin photoaging were retrieved from databases.The compound-potential target network and protein-protein interaction network were constructed to screen the key components and core targets. A photoaging cell model was established by irradiating HaCaT cells with medium-wave ultraviolet B （UVB）. The safe doses of bakuchiol （BAK） and salvianolic acid B （SAB） for treating HaCaT cells and the effects of BAK and SAB on the viability of cells exposed to UVB irradiation were determined by the cell counting kit-8 （CCK-8） method.The reactive oxygen species （ROS） fluorescent probe was used to measure the ROS production in the cells treated with BAK and SAB.The expression levels of genes related to oxidative stress，inflammation，collagen metabolism，and circadian rhythm clock were measured by Real-time PCR. ResultsA total of 24 transdermally absorbed components of MQEF were identified，which acted on 367 potential targets，and 417 targets related to skin photoaging were screened out，among which 47 common targets were predicted as the targets of MQEF in treating skin photoaging. MQEF exerted the anti-photoaging effect via key components such as BAK and SAB，which acted on core proteins such as serine/threonine kinase 1 （Akt1） and mitogen-activated protein kinase 3 （MAPK3） and intervened in core pathways such as the tumor necrosis factor （TNF） and phosphatidylinositol-3-kinase （PI3K）/protein kinase B （Akt） signaling pathways.Compared with the model group，the administration of BAK and SAB increased the survival rate of HaCaT cells （P<0.01），down-regulated the mRNA levels of cyclooxygenase-2 （COX-2），interleukin-6 （IL-6），tumor necrosis factor-α （TNF-α），matrix metalloproteinase-1 （MMP-1），and matrix metalloproteinase-9 （MMP-9） （P<0.01），and up-regulated the mRNA levels of heme oxygenase-1 （HO-1） and NAD（P）H quinone dehydrogenase 1 （NQO-1） （P<0.05，P<0.01） in photoaged HaCaT cells.In addition，it eliminated excess ROS production induced by UVB and up-regulated the mRNA levels of brain and muscle ARNT-like 1 （BMAL1） and circadian locomotor output cycles kaput （CLOCK） associated with circadian clock （P<0.05，P<0.01）. ConclusionMQEF delays skin photoaging through the coordinated effects of various components，multiple targets，and diverse pathways.The key components BAK and SAB in MQEF exhibit anti-photoaging properties，which involve inhibiting oxidative stress，preventing collagen degradation，mitigating inflammation，and maintaining normal skin circadian rhythms by regulating clock gene expression.

Immunoglobulin A nephropathy （IgAN） is the primary glomerulonephritis with the highest incidence rate in the world. It is also the main cause of end-stage renal disease （ESRD） in China， which has brought heavy economic burden to the society and patient families. Traditional Chinese medicine （TCM） has certain advantages in treating IgAN. In TCM， IgAN is classified into consumptive disease， hematuria， and edema categories， with the location in the kidney and involving the lung， liver， and spleen. Professor Ren Jixue， a master of TCM， believes that kidney deficiency and spleen deficiency are the root causes of IgAN， and the throat is the source of the disease. He proposed the theory of throat-kidney correlation and used the method of tonifying kidney and invigorating spleen as well as detoxifying and relieving sore-throat to treat IgAN， achieving significant therapeutic effects. Studies have shown that IgAN is closely related to mucosal immune defense. IgAN patients often experience recurrent and gradually worsening symptoms due to mucosal infections， and polymeric Ig receptor （PIgR） is an important component of mucosal defense function. The lack of PIgR leads to the accumulation of IgA molecules in the mucosal lamina propria， and the molecules enter the bloodstream in large quantities and ultimately deposit in the kidneys， causing kidney damage. Complement regulatory protein complement receptor type 1 （CR1） exists on red blood cells and glomeruli and has the function of inhibiting the activation and differentiation of B cells， clearing immune complexes， and inhibiting excessive activation of the complement system. Therefore， regulating the immune defense function through the mucosal-renal axis mediated by PIgR-CR1 will be an important target for preventing and treating IgAN. Based on the theory of throat-kidney correlation， this article explores the effects and molecular mechanisms of tonifying kidney and invigorating spleen as well as detoxifying and relieving sore-throat in preventing and treating IgAN by regulating the mucosal-kidney axis mediated by PIgR-CR1. It provides effective theoretical support and a scientific basis for TCM prevention and treatment of IgAN based on the theory of throat-kidney correlation.

Immunoglobulin A nephropathy （IgAN） is the primary glomerulonephritis with the highest incidence rate in the world. It is also the main cause of end-stage renal disease （ESRD） in China， which has brought heavy economic burden to the society and patient families. Traditional Chinese medicine （TCM） has certain advantages in treating IgAN. In TCM， IgAN is classified into consumptive disease， hematuria， and edema categories， with the location in the kidney and involving the lung， liver， and spleen. Professor Ren Jixue， a master of TCM， believes that kidney deficiency and spleen deficiency are the root causes of IgAN， and the throat is the source of the disease. He proposed the theory of throat-kidney correlation and used the method of tonifying kidney and invigorating spleen as well as detoxifying and relieving sore-throat to treat IgAN， achieving significant therapeutic effects. Studies have shown that IgAN is closely related to mucosal immune defense. IgAN patients often experience recurrent and gradually worsening symptoms due to mucosal infections， and polymeric Ig receptor （PIgR） is an important component of mucosal defense function. The lack of PIgR leads to the accumulation of IgA molecules in the mucosal lamina propria， and the molecules enter the bloodstream in large quantities and ultimately deposit in the kidneys， causing kidney damage. Complement regulatory protein complement receptor type 1 （CR1） exists on red blood cells and glomeruli and has the function of inhibiting the activation and differentiation of B cells， clearing immune complexes， and inhibiting excessive activation of the complement system. Therefore， regulating the immune defense function through the mucosal-renal axis mediated by PIgR-CR1 will be an important target for preventing and treating IgAN. Based on the theory of throat-kidney correlation， this article explores the effects and molecular mechanisms of tonifying kidney and invigorating spleen as well as detoxifying and relieving sore-throat in preventing and treating IgAN by regulating the mucosal-kidney axis mediated by PIgR-CR1. It provides effective theoretical support and a scientific basis for TCM prevention and treatment of IgAN based on the theory of throat-kidney correlation.

ObjectiveTo study the clinical characteristics and influencing factors of rheumatoid arthritis （RA） in the patients with cold dampness obstruction syndrome. MethodsThe RA patients treated in the Department of Traditional Chinese Medicine and Rheumatology of the China-Japan Friendship Hospital from August 2022 to June 2024 were selected. The demographic information， clinical data， laboratory test results， and traditional Chinese medicine （TCM） symptom information were collected for syndrome differentiation， on the basis of which the characteristics and influencing factors of cold dampness obstruction syndrome were analyzed. ResultsA total of 258 RA patients were selected in this study， including 88 （34.1%） patients with cold dampness obstruction syndrome， 53 （20.5%） patients with dampness and heat obstruction syndrome， 31 （12.0%） patients with wind dampness obstruction syndrome， 29 （11.2%） patients with liver-kidney deficiency syndrome， 19 （7.4%） patients with Qi-blood deficiency syndrome， 14 （5.4%） patients with phlegm-stasis obstruction syndrome， 15 （5.8%） patients with stasis obstructing collateral syndrome and 9 （3.5%） patients with Qi-Yin deficiency syndrome. The patients were assigned into two groups of cold dampness obstruction syndrome and other syndromes. The group of cold dampness obstruction syndrome had lower joint fever， 28-tender joint count （TJC28）， and 28-joint disease activity score （DAS28）-C-reactive protein （CRP） and higher central sensitization， cold feeling of joints， fear of wind and cold， cold limbs， and abdominal distention than the group of other syndromes （P<0.05）. The binary logistic regression analysis showed that central sensitization （OR 5.749， 95%CI 2.116-15.616， P<0.001） and DAS28-CRP （OR 0.600， 95% CI 0.418-0.862， P=0.006） were the independent factors influencing cold dampness obstruction syndrome in RA. ConclusionCold dampness obstruction syndrome is a common syndrome in RA patients. It is associated with central sensitization， cold feeling of joints， abdominal distension and may be a clinical syndrome associated with central sensitization.

Objective This study aims to investigate the effects of varying durations of light exposure on body weight and learning and memory abilities of pubertal NIH mice. Methods Forty pubertal NIH mice, evenly split by gender and with similar initial weights, were subjected to a 12 h light-dark cycle for one week. They were then randomly assigned to groups with daily light exposure durations of 0, 6, 12, 18, and 24 hours, with 8 mice in each group. The experimental period lasted for 7 weeks, with the first 5 weeks as the feeding phase under different light exposure conditions, and the last 2 weeks as the behavioral testing phase. Their body weight was monitored, and learning and memory abilities were assessed using the T-maze, object location test, and eight-arm maze tests. Results During the light exposure period, there were no significant differences in body weight among groups (P>0.05). However, the weight gain of mice in the 24 h group was significantly higher than that of the 0 h group and the 6 h group during the second and third weeks of light exposure (P<0.05). After five weeks of light exposure, in the T-maze test, the latency time of the 0 h light exposure group was significantly longer than that of the 12 h group (P<0.01), and the latency time of the 24 h light exposure group was significantly longer than that of the 12 h group (P<0.05). In the object location test, the mice in 12 h group exhibited a higher discrimination index and spent more time observing the new location compared to the other groups, with significant differences in comparison to the 18 h group (P<0.01) and the 24 h group (P<0.05). In the eight-arm maze test, the time to find food, the reference memory error rate, and the working memory error rate in the 12 h group were all lower than those in the 0 h group, with significant differences (P<0.05). Moreover, the working memory error rate in the 24 h group was higher than that in the 12 h group, with significant differences (P<0.05). Conclusion Continuous 24 h light exposure affects body weight gain, while light exposure durations exceeding 18 h or below 6 h per day weaken the learning and memory abilities of NIH mice.