Abelmoschi Corolla is extensively applied in managing diabetic nephropathy (DN) and other renal conditions due to its diuretic and detoxifying properties. The primary bioactive constituents of Abelmoschi Corolla are flavonoids, including notably rutin, hyperoside, isoquercitrin, hibifolin, myricetin, quercetin 3-O-β-D-glucuronide, and quercetin. These flavonoid components can influence the pathological progression of DN via a multi-target synergistic mechanism, effectively reducing proteinuria levels. This review examines the roles of Abelmoschi Corolla and its flavonoid components in modulating the key pathological aspects of DN and their underlying mechanisms, and briefly discusses the metabolic patterns of its bioactive components and the research progress in combined medication, aiming to provide a forward-looking scientific foundation for further investigating the molecular mechanisms and clinical applications of Abelmoschi Corolla in DN treatment.

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.

ObjectiveTaking the cuproptosis/oxidative stress pathway as the entry point， this study investigated the effect and mechanism of Liangyi Paste on hepatic lipid deposition in naturally aged mice fed with a high-fat diet. MethodsAfter adaptive feeding， 80 ten-week-old male C57BL/6 mice were used. Thirty of them were randomly divided into three groups （10 mice per group）： The 12-month-old control group （12MCON）， the 15-month-old control group （15MCON）， and the 15-month-old group with a high-fat diet （15MHFD）. The 12MCON and 15MCON groups were continuously fed a standard diet， while the 15MHFD group started receiving a high-fat diet at 12 months of age. Tissue samples were collected at the corresponding time points for each group. The remaining 50 mice were randomly divided into five groups （10 mice per group）： the 20-month-old control group （20MCON）， the model group， and the low-， medium-， and high-dose Liangyi Paste groups （2.91 ， 5.82 ， 11.64 g·kg^-1·d^-1， respectively）. The 20MCON group was continuously fed a standard diet， while the other groups started receiving a high-fat diet at 15 months of age. At 18 months of age， the Liangyi Paste groups were administered the corresponding doses of Liangyi Paste by gavage， while the 20MCON and model groups were given an equal volume of saline by gavage. After 8 weeks of continuous gavage （when the mice reached 20 months of age）， tissue samples were collected. Hepatic TG levels were measured using assay kits； liver histology and lipid deposition were observed via hematoxylin-eosin （HE） and oil red O staining； reactive oxygen species （ROS） were detected by enzyme-linked immunosorbent assay （ELISA）； Cu²⁺， superoxide dismutase （SOD）， and malondialdehyde （MDA） levels were measured by colorimetry； mRNA and protein expression of genes related to cuproptosis and oxidative stress pathways were analyzed by Real-time polymerase chain reaction（Real-time PCR） and Wes automated protein expression system. ResultsCompared with 12MCON， the 15MCON group showed significantly increased hepatic TG， Cu²⁺， ROS， and MDA levels （P<0.01）， decreased SOD （P<0.01）， hepatocyte swelling， and disordered arrangement. The mRNA and protein levels of ferredoxin 1 （FDX1）， dihydrolipoamide S-acetyltransferase （DLAT）， heat shock protein 70 （HSP70）， dihydrolipoamide dehydrogenase （DLD）， pyruvate dehydrogenase E1 subunit-β （PDHB）， nuclear factor erythroid 2-related factor 2 （Nrf2）， and peroxisome proliferator-activated receptor γ （PPARγ） were significantly elevated （P<0.05， P<0.01）. Compared with 15MCON group， the 15MHFD and 20MCON groups exhibited further increases in TG， Cu²⁺， ROS， and MDA （P<0.01）， reduced SOD （P<0.01）， and aggravated hepatocyte swelling and disorder. There were increased lipid droplets with mild vacuolization in the 15MHFD group， and no significant lipid deposition was observed in the 20MCON group. FDX1， DLAT， HSP70， DLD， PDHB， Nrf2， and PPARγ mRNA and protein levels were significantly increased （P<0.05， P<0.01）. Compared with 20MCON group， the model group demonstrated markedly elevated TG， Cu²⁺， ROS， and MDA （P<0.01）， reduced SOD （P<0.01）， severe hepatic steatosis， and upregulated expression of FDX1， DLAT， HSP70， DLD， PDHB， Nrf2， and PPARγ mRNA and proteins （P<0.05， P<0.01）. All abnormalities were significantly reversed after Liangyi Paste treatment. ConclusionLiangyi paste can ameliorate hepatic lipid deposition in naturally aged mice with a high-fat diet by modulating the cuproptosis/oxidative stress pathway.

Objective To implement the disease prevention and control strategy of being ^"proactive and grassroots-focused,^" and to enhance the overall effectiveness of general hospitals in the tertiary prevention of cervical cancer, this consensus aims to provide an actionable guiding framework for the standardized construction of ^"Integrated Outpatient Clinics for Cervical Cancer Prevention and Control^" in general hospitals at all levels. Methods This consensus systematically elaborates on the specific elements for establishing such integrated clinics and formulates the corresponding standards. Results It is anticipated that the consensus will promote the establishment of standardized, homogeneous, and high-efficiency frontline positions for cervical cancer prevention and control within general hospitals, thereby contributing to the strategic vision of accelerating the elimination of cervical cancer. Conclusion The formulation and promotion of the consensus aim to provide robust clinical practice support for accelerating the realization of China's strategic vision of eliminating cervical cancer.

BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

Background: Despite the rising incidence of end-stage renal disease (ESRD) among individuals with type 2 diabetes mellitus (T2DM) in Korea, no predictive model or nomogram has been developed using a nationwide cohort. In this study, we developed a nomogram to predict the long-term risk of ESRD in patients with T2DM using a large-scale, population-based Korean database. Methods: Using the Korean National Health Insurance Database, patients with T2DM who underwent health examinations between 2015 and 2016 were assigned as development (n=1,744,277) and validation (n=747,407) cohorts. New ESRD cases were identified using codes for renal replacement therapy. A Cox proportional hazards regression model was used to derive a risk-scoring system, and 13 variables were selected. A risk score nomogram was then created to estimate the risk of ESRD. Results: In the development cohort, 8,631 patients with T2DM developed ESRD during a follow-up period of 4.8±0.9 years. After multivariable adjustment, significant predictors of ESRD included male sex, current smoking, physical inactivity, low income, low body mass index, hypertension, low-density lipoprotein cholesterol ≥160 mg/dL, chronic kidney disease, insulin use, and longer duration of T2DM. A final nomogram incorporating 13 variables was developed to estimate the individual probability of ESRD. The concordance index for ESRD prediction in the validation cohort was 0.906 (95% confidence interval, 0.9 to 0.912). Conclusion This 13-variable nomogram provides a simple tool for identifying patients with T2DM at high risk of ESRD and may aid in early intervention.

ObjectiveTo investigate the effects of modified Ditan tang on genes related to the transcription-translation feedback loop （TTFL） of biorhythm in the rat model of non-alcoholic fatty liver disease （NAFLD） and its mechanism for prevention and treatment of NAFLD. MethodsSixty-five healthy SPF male SD rats were randomly assigned into blank （n=20）， model （n=15）， and low-， medium-， and high-dose （2.68， 5.36， and 10.72 g·kg^-1·d^-1， respectively） modified Ditan tang （n=10） groups. Other groups except the blank group were fed a high-fat diet for 12 weeks. The modified Ditan tang groups were treated with the decoction at corresponding doses by gavage， and the blank and model groups were treated with an equal volume of normal saline from the 9th week for 4 weeks. The levels of triglyceride （TG）， total cholesterol （TC）， low-density lipoprotein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， aspartate aminotransferase （AST）， and alanine aminotransferase （ALT） in the serum were measured by an automatic biochemical analyzer. TG and non-esterified fatty acid （NEFA） assay kits were used to measure the levels of TG and NEFA in the liver. The pathological changes in the hypothalamus and liver were observed by hematoxylin-eosin staining， and the lipid deposition in the liver was observed by oil red O staining. The levels of brain-muscle ARNT-like protein 1 （BMAL1/ARNTL） in the hypothalamus and liver were determined by immunohistochemical staining. The mRNA and protein levels of BMAL1， circadian locomotor output cycles kaput （CLOCK）， period circadian clock 2 （PER2）， and cryptochrome1 （Cry1） in the hypothalamus and liver were determined by Real-time PCR and Western blot， respectively. ResultsCompared with the blank group， the model group showed elevated levels of TG， TC， LDL-C， AST， and ALT （P<0.01） and a lowered level of HDL-C （P<0.05） in the serum， elevated levels of TG and NEFA in the liver （P<0.01）， pyknosis and deep staining of hypothalamic neuron cells， and a large number of vacuoles in the brain area. In addition， the model group showed lipid deposition in the liver， up-regulated mRNA and protein levels of CLOCK and BMAL1 （P<0.01）， and down-regulated mRNA and protein levels of Cry1 and PER2 （P<0.01） in the hypothalamus and liver. Compared with the model group， all the three modified Ditan tang groups showed lowered levels of TG， TC， LDL-C， ALT， and AST （P<0.05， P<0.01） and an elevated level of HDL-C （P<0.05） in the serum， and lowered levels of TG and NEFA （P<0.05， P<0.01） in the liver. Furthermore， the three groups showed alleviated pyknosis and deep staining of hypothalamic neuron cells， reduced lipid deposition in the liver， down-regulated mRNA and protein levels of CLOCK and BMAL1 （P<0.05， P<0.01）， and up-regulated mRNA and protein levels of Cry1 and PER2 （P<0.05， P<0.01） in the hypothalamus and liver. ConclusionModified Ditan tang can reduce lipid deposition in the liver and regulate the expression of CLOCK， BMAL1， Cry1， and PER2 in the TTFL of NAFLD rats.