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.

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.

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.

Calcium-based biomaterials have been intensively studied in the field of drug delivery owing to their excellent biocompatibility and biodegradability. Calcium-based materials can also deliver contrast agents, which can enhance real-time imaging and exert a Ca²⁺-interfering therapeutic effect. Based on these characteristics, amorphous calcium carbonate (ACC), as a brunch of calcium-based biomaterials, has the potential to become a widely used biomaterial. Highly functional ACC can be either discovered in natural organisms or obtained by chemical synthesis However, the standalone presence of ACC is unstable in vivo. Additives are required to be used as stabilizers or core-shell structures formed by permeable layers or lipids with modified molecules constructed to maintain the stability of ACC until the ACC carrier reaches its destination. ACC has high chemical instability and can produce biocompatible products when exposed to an acidic condition in vivo, such as Ca²⁺ with an immune-regulating ability and CO₂ with an imaging-enhancing ability. Owing to these characteristics, ACC has been studied for self-sacrificing templates of carrier construction, targeted delivery of oncology drugs, immunomodulation, tumor imaging, tissue engineering, and calcium supplementation. Emphasis in this paper has been placed on the origin, structural features, and multiple applications of ACC. Meanwhile, ACC faces many challenges in clinical translation, and long-term basic research is required to overcome these challenges. We hope that this study will contribute to future innovative research on ACC.

ObjectiveTo investigate the possible mechanism of Shenqi Jianxin Formula （参芪健心方） in the treatment of chronic heart failure （CHF） from the perspective of pyroptosis. MethodsFifty-two rats were randomly divided into sham operation group （n=8） and modeling group （n=44）. In the modeling group， the anterior descending branch of the left coronary artery was ligated to construct CHF rat model. Forty successfully-modelled rats were randomly divided into model group， Entresto group， Shenqi Jianxin Formula group， MCC950 group and the combination group （Shenqi Jianxin Formula plus MCC950）， with 8 rats in each group. In Shenqi Jianxin Formula group， 7.4 g/（kg·d） of Shenqi Jianxin Formula was given by gavage， while in Entresto group， 68 mg/（kg·d） of Entresto suspension was given by gavage； in MCC950 group， MCC950 was injected intraperitoneally with 10 mg/kg once every other day， and in the combination group， 7.4 g/（kg·d） of Shenqi Jianxin Formula was given by gavage， and MCC950 was injected intraperitoneally with 10 mg/kg once every other day； 10 ml/（kg·d） of saline was given by gavage in the sham operation group and the model group. After 3 weeks of continuous intervention， serum brain B-type natriuretic peptide （BNP）， creatine kinase isoenzyme MB （CK-MB）， interleukin 1β （IL-1β）， and interleukin 18 （IL-18） levels were detected by ELISA； HE staining and MASSON staining were used to observe pathological changes in rat myocardium. Except for the Entresto group， western blot technique was used to detect the expression of NOD-like receptor protein 3 （NLRP3）， caspase-1， and apoptosis-associated speck-like protein possessing a caspase-recruiting domain （ASC）； RT-PCR was used to detect the expression of NLRP3 and caspase-1 mRNA. ResultsCompared with the sham operation group， HE staining of rats in the model group showed obvious myocardial injury， while MASSON staining showed increased area of collagen fibrosis， and serum BNP， CK-MB， IL-1β， IL-18， myocardial tissue NLRP3， caspase-1， ASC protein expression and NLRP3， caspase-1 mRNA expression were all elevated （P＜0.05）. Compared with those in the model group， cardiomyocyte injury of rats and collagen fibrosis area were reduced， and serum BNP， CK-MB， IL-1β， and IL-18 contents were all reduced in Shenqi Jianxin Formula group， Entresto group， MCC950 group， and the combination group； except for Entresto group， myocardial tissue NLRP3， caspase-1， ASC protein expression and NLRP3， caspase-1 mRNA expression were reduced in the remaining three medication group （P＜0.05）. Compared with Shenqi Jianxin Formula group， the MCC950 group and the combination group showed decreased serum IL-1β and IL-18 content， collagen fibrosis area， myocardial tissue NLPR3， caspase-1 protein expression， and caspase-1 mRNA expression， and decreased ASC and NLRP3 mRNA expression was shown in the combination group （P＜0.05）. Compared with MCC950 group， collagen fibrosis area was reduced， and serum IL-18 content， NLRP3， caspase-1 mRNA expression were reduced in the combination group （P＜0.05）. ConclusionShenqi Jianxin Formula can effectively improve the myocardial injury and heart failure in rats with CHF， and its mechanism may be related to the inhibition of cardiomyocyte pyroptosis through NLPR3/Caspase-1 pathway to reduce the level of intramyocardial inflammation. The combined use of MCC950 with Shenqi Jianxin Formula could more effectively inhibite myocardial pyroptosis， with better therapeutic result than single use of each part.

Objective:To investigate the association of serum uric acid (SUA) with the outcome in patients with acute ischemic stroke (AIS) at one year after onset.Methods:Patients with AIS admitted to the Department of Neurology, Dagang Hospital, Tianjin Binhai New Area were included retrospectively. According to the modified Rankin Scale (mRS) score at 1 year after onset, patients were divided into a good outcome group (0-2) and a poor outcome group (>2). They were also divided into a survival group and a death group based on their survival status at 1 year after onset. The clinical baseline data and laboratory tests were compared. Multivariate logistic regression analysis was used to determine the associations of SUA with poor outcome and death in patients with AIS. Results:A total of 651 patients were enrolled, including 430 males (66.1%) aged 67.5±11.7 years. Four hundred and fourteen patients (63.6%) were in the good outcome group, and 237 (36.4%) were in the poor outcome group. There were 568 patients (87.3%) in the survival group and 43 (16.7%) in the death group. Univariate analysis showed that there were differences in age, atrial fibrillation, history of stroke or transient ischemic attack, baseline National Institutes of Health Stroke Scale (NIHSS) score, and pre-admission mRS score between the poor outcome group and the good outcome group. The homocysteine, SUA, white blood cell count, and creatinine in the poor outcome group were higher than those in the good outcome group, while the red blood cell count and hemoglobin were lower than those in the good outcome group (all P<0.05). There were differences in age, history of ischemic heart disease, atrial fibrillation, history of stroke or transient ischemic attack, baseline NIHSS score, pre-admission mRS score, and stroke etiology classification between the survival group and the death group. Hemoglobin and triglycerides in the survival group were higher than those in the death group, while the white blood cell count and creatinine were lower than those in the death group (all P<0.05). Multivariate logistic regression analysis showed that SUA was an independent risk factor for poor outcome in patients with AIS (odds ratio 1.004, 95% confidence interval 1.001-1.006; P<0.01), but there was no independent correlation with death. Conclusion:Higher SUA is an independent risk factor for poor outcome at one year after onset in patients with AIS.