Xiang thinking is a cognitive approach that reflects the relationships between phenomena and their underlying principles by analyzing their external manifestations through methods such as analogy， reasoning， deduction， and symbolism. This article applied xiang thinking to analyze the etiology and pathogenesis of "wind， fire， phlegm， and blood stasis" in stroke， thereby exploring its impact on the principles of syndrome differentiation and treatment of this condition. Meanwhile， the article traced the construction process of xiang thinking， and interpreted the concept of "toxin pathogen" in traditional Chinese medicine from four perspectives， state， attribute， origin， and law. Furthermore， the relationship between the process of constructing xiang thinking and the origin of etiology， identification methods， pathogenesis evolution， and treatment strategies for stroke with syndrome of combined blood stasis and toxin was explored， so as to provide insights into research on the etiology and pathogenesis of stroke， as well as clinical diagnosis and treatment approaches.

Breast cancer is a kind of malignant tumor with a complex mechanism， and its morbidity and mortality are increasing year by year， which seriously threatens women's health. At present， the main clinical treatments are surgical resection， radiotherapy， chemotherapy， and drug therapy， but they are often accompanied by side effects and adverse reactions， which affect the therapeutic effect. Traditional Chinese medicine （TCM） has the advantages of multi-component and multi-target treatment in the fight against breast cancer. The wnt/β-catenin signaling pathway is one of the classic pathways in cancer research. Abnormally activated Wnt/β-catenin signaling pathway inhibits β-catenin degradation by blocking the formation of Axin/glycogen synthase kinase 3β/adenomatous polyposis coli complex， thus promoting β-catenin nuclear metastasis， and it binds to T cell transcription factor/lymphoenhancer factor-1 to initiate downstream target genes and further interfere with the proliferation， migration， and invasion of tumor cells to affect the tumor process. Previous studies have shown that TCM monomers and compounds can mediate the Wnt/β-catenin signaling pathway to inhibit the malignant phenotype of breast cancer cells， thus playing an anti-breast cancer role， and the biochemical process involved in the regulation of therapeutic drugs has not been systematically combed. By analyzing and collating Chinese and foreign literature at the present stage， this paper discussed the association mechanism between Wnt/β-catenin signaling pathway and breast cancer and analyzed the internal mechanism of TCM monomers and compounds in mediating Wnt/β-catenin signaling pathway to exert anti-breast cancer effect. The statistical results showed that the flavonoids， alkaloids， and terpenoids in TCM monomers could target the Wnt/β-catenin signaling pathway and block the further development of malignant phenotype of breast cancer cells. TCM compounds with functions of clearing heat and detoxifying， promoting blood circulation and removing blood stasis， and tonifying kidney and liver were commonly used to intervene in the Wnt/β-catenin signaling pathway to prevent breast cancer. Compared with the current inhibitors of Wnt/β-catenin signaling pathway， the application of TCM monomers and compounds is expected to bring low-toxicity and high-efficiency breast cancer treatment drugs to the clinical practice， and the existing results provide a reference for the subsequent screening， research， and development of TCM small-molecule compounds and TCM compounds against breast cancer.

The liver is closely associated with inflammation and the redox response， and inflammation is the body's innate defense system for clearing away harmful stimuli and participating in the liver's wound-healing response.Oxidative stress is associated with the activation of inflammatory pathways， and sustained inflammation and the corresponding regenerative wound healing response can induce fibrosis， cirrhosis， progression to end-stage liver disease or hepatocellular carcinoma， and ultimately death.Some "medicine and food homology" traditional Chinese medicine has been used in clinical effect， showing the ability to protect the liver.This paper reviewed the relationship between liver and oxidative stress response and inflammation response， and sorted out 110 "medicine and food same origin" traditional Chinese medicines based on the Chinese Pharmacopoeia（2020 edition） and the Chinese materia medica.The results showed that common floweringqince fruit， licorice root， cassia seed， emblic，seabuckthorn fruit，Chinese date， honeysuckle， ginger， cape jasmine fruit， platycodon root， lotus leaf， dandelion， reed root， honey， mountain honeysuckle， milkvetch root， glossy ganoderma， Gastrodia gastrodia and eucommia leaf were recorded to have liver protection effects.The liver protection mechanism is mainly anti-inflammatory， antioxidant and lipid peroxidation inhibition. Some Chinese herbs can also play a liver protection role by inhibiting the growth of hepatitis virus and liver cancer cells and regulating bile acid metabolism.In addition， the biological mechanism of its liver protection effect through antioxidant and anti-inflammatory effects in animal experiments was analyzed， and it was found that it plays a role through multiple pathways and multiple targets， providing new ideas for the role of "medicine and food homology" traditional Chinese medicine in the treatment strategy of liver diseases.

The liver is closely associated with inflammation and the redox response， and inflammation is the body's innate defense system for clearing away harmful stimuli and participating in the liver's wound-healing response.Oxidative stress is associated with the activation of inflammatory pathways， and sustained inflammation and the corresponding regenerative wound healing response can induce fibrosis， cirrhosis， progression to end-stage liver disease or hepatocellular carcinoma， and ultimately death.Some "medicine and food homology" traditional Chinese medicine has been used in clinical effect， showing the ability to protect the liver.This paper reviewed the relationship between liver and oxidative stress response and inflammation response， and sorted out 110 "medicine and food same origin" traditional Chinese medicines based on the Chinese Pharmacopoeia（2020 edition） and the Chinese materia medica.The results showed that common floweringqince fruit， licorice root， cassia seed， emblic，seabuckthorn fruit，Chinese date， honeysuckle， ginger， cape jasmine fruit， platycodon root， lotus leaf， dandelion， reed root， honey， mountain honeysuckle， milkvetch root， glossy ganoderma， Gastrodia gastrodia and eucommia leaf were recorded to have liver protection effects.The liver protection mechanism is mainly anti-inflammatory， antioxidant and lipid peroxidation inhibition. Some Chinese herbs can also play a liver protection role by inhibiting the growth of hepatitis virus and liver cancer cells and regulating bile acid metabolism.In addition， the biological mechanism of its liver protection effect through antioxidant and anti-inflammatory effects in animal experiments was analyzed， and it was found that it plays a role through multiple pathways and multiple targets， providing new ideas for the role of "medicine and food homology" traditional Chinese medicine in the treatment strategy of liver diseases.

Six compounds were isolated from the ethyl acetate fraction of Citri Sarcodactylis Fructus by using various column chromatographic methods, such as MCI Gel CHP-20, ODS, Sephadex LH-20, silica gel and semipreparative HPLC. Their structures were identified to be citrusin G (1), citrusin H (2), citrusin E (3), syringin (4), coniferin (5), methylconiferin (6) by NMR, HR-ESI-MS, UV, IR spectra. Compounds 1 and 2 were new secondary metabolism products and 3-6 were obtained from the titled material for the first time. Compound 1 showed anti-renal fibrosis activity in TGF-β1-induced kidney proximal tubular cells.

ObjectiveA multiplex amplification system was constructed based on the capillary electrophoresis platform for simultaneous detection of saliva, semen, and vaginal secretions using tissue-specific RNA markers. The aim of this study is to identify the tissue origin of suspicious body fluid stains found at crime scenes and determine whether the body fluid stains at the crime scene are one or several types among saliva, semen, and vaginal secretions. MethodsThirty saliva samples, forty semen samples, and forty vaginal secretion samples (half from 2015 and half from 2024) were collected from healthy adult volunteers. Through primer designing, system formulation, and PCR condition optimization, a multiplex fluorescent amplification system was constructed. The specificity, sensitivity, and detection ability for mixed samples of this system were investigated, and it was tested using real crime scene materials. In the primer design stage, to reduce the requirements for RNA template quality, the amplification products were set within 80-300 bp. In the system formulation stage, dominant and subordinate primers were mainly considered. By reducing the concentration of dominant primers and increasing that of subordinate primers, a capillary electrophoresis spectrum with an appropriate peak height ratio was finally obtained. Additionally, gradient experiments were designed to adjust the concentrations of PCR reagents and PCR amplification conditions, and multiple versions of DNA amplification enzymes were optimized to achieve the best experimental results. ResultsThrough statistical analysis, there was no significant difference in the capillary electrophoresis of the 3 types of body fluid samples from the two years (2015 and 2024), demonstrating that the sample preservation method in this study can preserve samples for a relatively long time. The composite amplification system constructed in this study exhibited high specificity for all 3 types of body fluid, with no cross-reactions between the markers of each type of body fluid. The minimum detection thresholds for the 3 types of body fluid reached 0.002 9, 0.001 5, and 0.42 mg/L, respectively. This system also had a high degree of discrimination for mixed samples, especially for semen-saliva mixtures, where each body fluid marker could still be successfully detected when the concentration ratio of semen to saliva was 100:1. Meanwhile, in the two actual cases presented in this article, the application of this composite amplification system performed outstandingly. ConclusionThe composite amplification detection system constructed in this study can achieve the correct screening of saliva, semen, and vaginal secretions, overcoming the problems such as low specificity and sensitivity of marker tests and unbalanced RFU values of each marker in previous studies. The specificity and sensitivity meet the practical work requirements, and the operation is simple. It provides an analytical and identification method for body fluid stains in actual case and is applicable to the identification of the tissue origin of biological evidence at crime scenes involving sexual assault, indecent assault, and other criminal acts. In the future, more types of body fluid markers will be screened to expand the types of body fluids detected by the system, and body fluid-specific cSNP and cInDel genetic markers will be introduced to infer the sources (individuals and types) of mixed and complex stains more accurately.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.