Tracheobronchial adenoid cystic carcinoma （TACC） is a low-grade malignant tumor originating from the airway mucosa. Despite its slow progression，it is characterized by high invasiveness，frequent recurrence，and a strong tendency for metastasis. Preclinical studies have shown that vascular-targeted therapy holds significant potential. However，an effective systemic treatment for TACC has not been established yet. This study explored TACC from the perspective of "Feiji" in traditional Chinese medicine （TCM） as the starting point. It deeply investigated the mechanisms of abnormal collaterals and tumor vascular recruitment and further elaborated on the theoretical connection between abnormal collaterals and tumor vascular recruitment. Firstly，collateral hyperactivity led to disordered and erratic pulmonary collaterals. Their abnormal structures were similar to the disorderly and tortuous nature of tumor （pseudo）angiogenesis. This resulted in imbalances in the functions of circulation，perfusion，and reverse injection of the pulmonary collaterals，and then led to unrestrained collateral dysfunction and the accumulation of pathogenic factors. Secondly，the remodeling of the extracellular matrix （ECM） and epithelial-mesenchymal transition （EMT） in TACC were critical processes in vascular co-option （VCO），representing the micro-level manifestation of the displacement of nutrient and defense. During this process，ECM remodeling made TACC cells more likely to hijack normal blood vessels，creating a complex vascular microenvironment conducive to tumor growth. In terms of treatment，this study proposed a TCM strategy of "regulating collaterals to expel pathogenic factors and nourishing collaterals to strengthen the healthy Qi"，and listed potential TCM. These were intended to regulate the Qi and blood in the collaterals，repair the functions of abnormal collaterals，and intervene in the vascular recruitment process of TACC. Future research should focus on improving the TCM clinical syndrome characteristics of TACC. Through modern molecular biology techniques，it is necessary to deeply analyze the micro-level pattern of vascular recruitment in TACC. This would enrich the understanding of the profound connection between abnormal collaterals and tumor vascular recruitment，providing empirical evidence for TCM-targeted therapies for vascular recruitment in TACC.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

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.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

ObjectiveTo explore the correlation between the occurrence of cardiovascular events in rheumatoid arthritis（RA） and traditional Chinese medicine（TCM） syndrome. MethodsThe cross-sectional study selected 6713 RA patients from 122 centres nationwide， in which general information such as name， gender， age， height， body weight， and course of disease were collected by completing a questionnaire； patients were classified into eight types of syndrome according to the information of their four examinations，i.e. wind-dampness obstruction syndrome， cold-dampness obstruction syndrome， dampness-heat obstruction syndrome， phlegm-stasis obstruction syndrome， stasis-blood obstructing collateral syndrome， qi-blood deficiency syndrome， liver-kidney insufficiency syndrome， and qi-yin deficiency syndrome. According to the occurrence of cardiovascular events， they were divided into the occurrence group and the non-occurrence group， and the condition assessment data and laboratory examination indexes were recorded. The test of difference between groups was used to analyse the possible risk factors for the occurrence of RA cardiovascular events， and binary logistic regression was used to analyse the correlation between TCM syndromes and RA cardiovascular events. ResultsA total of 6713 RA patients were included， including 256 cases in occurrence group and 6457 in non-occurrence group. There was no statistically significant difference between groups in terms of height， gender， insomnia， appetite， white blood cell（WBC）， hemoglobin（HGB）， platelets（PLT）， rheumatoid factor（RF）， anti-cyclic peptide containing citrulline（CCP）， alanine aminotransferase（ALT）， aspartate aminotransferase（AST）， γ-glutamyl transpeptidase（GGT）， urea creatinine（CREA）， and glucose（GLU）（P＞0.05）. The TCM syndromes between groups showed significant statistic differences（P＜0.05）. Patients in occurrence group had longer disease duration， heavier body weight， and older age； more severe conditions such as disease activity（DAS-28）， number of painful joints（TJC）， number of swollen joints（SJC）， health questionnaire scores（HAQ）， visual analog scores（VAS）， restlessness， and fatigue； higher blood sedimentation rate（ESR）， low-density lipoprotein（LDL-C）， triglyceride（TG）， total cholesterol（TC）， D-Dimer， and lower high-density lipoprotein（HDL-C）（P＜0.05）. The distribution of syndrome types showed that dampness-heat obstruction syndrome accounted for the largest proportion of patients in both groups and was higher in RA cardiovascular events. Logistic regression analysis showed that the occurrence of RA cardiovascular events was strongly associated with dampness-heat obstruction syndrome［OR=5.937， 95%CI （4.434， 7.949）， P＜0.001］. ConclusionThe occurrence of RA cardiovascular events were associated with TCM syndromes， and the probability of cardiovascular events in the RA patients with dampness-heat obstruction syndrome was 5.937 times higher than patients with other TCM syndromes.

The chemical constituents of Commiphora myrrha was investigated by column chromatography on silica gel, ODS, Sephadex LH-20, and semi-preparative HPLC. Their structures were elucidated by comprehensive spectroscopic methods including UV, IR, MS, NMR, as well as ECD calculation. Seven compounds were isolated from the dichloromethane-soluble fraction of C. myrrha and their structures were identified as(1S,2R,4S,5R,8S)-guaiane-2-hydroxy-7(11),10(15)-dien-6-oxo-12,8-olide(1), commipholide E(2), myrrhterpenoid H(3), myrrhterpenoid I(4), myrrhterpenoid E(5), 2α-methoxy-8α-hydroxy-6-oxogermacra-1(10),7(11)-dien-8,12-olide(6), 8,12-epoxy-1α,9α-hydroxy-eudesma-7,11-diene-6-dione(7). Compound 1 was a new compound and named myrrhterpenoid P. Compound 7 was isolated from Commiphora genus for the first time. Compounds 2, 5, and 6 significantly inhibited nitric oxide(NO) production in LPS-stimulated RAW264.7 cells, with IC_(50) values of(49.67±4.16),(40.80±1.27),(47.22±0.87) μmol·L~(-1), respectively [indomethacin as the positive control, with IC_(50) value of(63.92±2.60) μmol·L~(-1)].
Commiphora/chemistry* ; Animals ; Mice ; Resins, Plant/chemistry* ; Sesquiterpenes/isolation & purification* ; Molecular Structure ; Nitric Oxide ; Macrophages/metabolism* ; RAW 264.7 Cells ; Drugs, Chinese Herbal/pharmacology*

Basket trial, as an innovative clinical trial design concept, marks the transformation of medical research from the traditional large-scale and single-disease treatment to the precise and individualized treatment. By gradually incorporating the Bayesian method during development, the trial design becomes more scientific and reasonable and increases its efficiency. The fundamental principle of the Bayesian method is the utilization of prior knowledge in conjunction with new observational data to dynamically update the posterior probability. This flexibility enhances the basket trial's capacity to effectively adapt to variations during the research process. Consequently, it enables researchers to dynamically adjust research strategies based on accumulated data and improve the predictive accuracy regarding treatment responses. In addition, the design concept of the basket trial aligns with the traditional Chinese medicine(TCM) principle of "homotherapy for heteropathy". The principle of "homotherapy for heteropathy" emphasizes that under certain conditions, different diseases may have the same treatment. Similarly, basket trials allow using a uniform trial design across multiple diseases, offering enhanced operational and significant practical value in the realm of TCM, particularly within the context of syndrome-based disease research. By introducing basket trials, the design of TCM clinical studies will be more scientific and yield higher-quality evidence. This study systematically categorized various Bayesian methods and models utilized in basket trials, evaluated their strengths and weaknesses, and identified their appropriate application contexts, so as to offer a practical guide for designing basket trials in the realm of TCM.
Bayes Theorem ; Humans ; Medicine, Chinese Traditional/methods* ; Research Design ; Clinical Trials as Topic/methods* ; Drugs, Chinese Herbal/therapeutic use*

This study identified blood-entering components of Anshen Dropping Pills and explored their anti-insomnia effects and mechanisms. The main blood-entering components of Anshen Dropping Pills were detected and identified by UPLC-Q-TOF-MS/MS. The rationality of the formula was assessed by using enrichment analysis based on the relationship between drugs and symptoms, and core targets of its active components were selected as the the potential anti-insomnia targets of Anshen Dropping Pills through network pharmacology analysis. Furthermore, protein-protein interaction(PPI) network, Gene Ontology(GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were performed on the core targets. An active component-core target network for Anshen Dropping Pills was constructed. Finally, the effects of low-, medium-, and high-dose groups of Anshen Dropping Pills on sleep episodes, sleep duration, and sleep latency in mice were measured by supraliminal and subliminal pentobarbital sodium experiments. Moreover, total scores of the Pittsburgh sleep quality index(PSQI) scale was used to evaluate the changes before and after the treatment with Anshen Dropping Pills in a clinical study. The enrichment analysis based on the relationship between drugs and symptoms verified the rationality of the Anshen Dropping Pills formula, and nine blood-entering components of Anshen Dropping Pills were identified by UPLC-Q-TOF-MS/MS. The network proximity revealed a significant correlation between eight components and insomnia, including magnoflorine, liquiritin, spinosin, quercitrin, jujuboside A, ginsenoside Rb_3, glycyrrhizic acid, and glycyrrhetinic acid. Network pharmacology analysis indicated that the major anti-insomnia pathways of Anshen Dropping Pills involved substance and energy metabolism, neuroprotection, immune system regulation, and endocrine regulation. Seven core genes related to insomnia were identified: APOE, ALB, BDNF, PPARG, INS, TP53, and TNF. In summary, Anshen Dropping Pills could increase sleep episodes, prolong sleep duration, and reduce sleep latency in mice. Clinical study results demonstrated that Anshen Dropping Pills could decrease total scores of PSQI scale. This study reveals the pharmacodynamic basis and potential multi-component, multi-target, and multi-pathway effects of Anshen Dropping Pills, suggesting that its anti-insomnia mechanisms may be associated with the regulation of insomnia-related signaling pathways. These findings offer a theoretical foundation for the clinical application of Anshen Dropping Pills.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Tandem Mass Spectrometry/methods* ; Sleep Initiation and Maintenance Disorders/metabolism* ; Mice ; Network Pharmacology ; Male ; Chromatography, High Pressure Liquid ; Humans ; Protein Interaction Maps/drug effects* ; Sleep/drug effects* ; Female ; Adult