Cardiovascular diseases and psychological disorders represent two major threats to human physical and mental health. Research on electrocardiogram (ECG) signals offers valuable opportunities to address these issues. However, existing methods are constrained by limitations in understanding ECG features and transferring knowledge across tasks. To address these challenges, this study developed a multi-resolution feature encoding network based on residual networks, which effectively extracted local morphological features and global rhythm features of ECG signals, thereby enhancing feature representation. Furthermore, a model compression-based continual learning method was proposed, enabling the structured transfer of knowledge from simpler tasks to more complex ones, resulting in improved performance in downstream tasks. The multi-resolution learning model demonstrated superior or comparable performance to state-of-the-art algorithms across five datasets, including tasks such as ECG QRS complex detection, arrhythmia classification, and emotion classification. The continual learning method achieved significant improvements over conventional training approaches in cross-domain, cross-task, and incremental data scenarios. These results highlight the potential of the proposed method for effective cross-task knowledge transfer in ECG analysis and offer a new perspective for multi-task learning using ECG signals.
Humans ; Electrocardiography/methods* ; Mental Health ; Algorithms ; Signal Processing, Computer-Assisted ; Machine Learning ; Arrhythmias, Cardiac/diagnosis* ; Cardiovascular Diseases ; Neural Networks, Computer ; Mental Disorders

ChuanWu (CW), the dried mother root of Aconitum carmichaelii Debx., is a well-known traditional Chinese medicine (TCM) recognized for its potent efficacy but inherent toxicity, primarily due to its alkaloid content. Traditional and modern detoxification methods for CW include proper processing, rational compatibility, and specialized decoction techniques, among which honey-boiled CW is particularly distinctive. However, research on the detoxification mechanism of honey-boiled CW remains limited. This study investigated this mechanism by analyzing alkaloid transformation and supramolecular aggregation. Honey-boiled and water-boiled CW preparations were compared. Ultra-high-performance liquid chromatography-tandem mass spectrometry was used to analyze CW alkaloids, specifically diester alkaloids (DDAs), monoester alkaloids (MDAs), and non-esterified diterpenoid alkaloids (NDAs). Transmission electron microscopy was employed to observe and identify supramolecular aggregates in the honey-boiled CW decoction. In vivo absorption of water-boiled, honey-boiled, and NADES-boiled CW was compared. Median lethal dose (LD₅₀) tests assessed toxicity, including hepatotoxicity and nephrotoxicity. In vitro experiments evaluated the safety, anti-inflammatory, and analgesic effects of CW-medicated serum on RAW264.7 cells, with in vivo validation in mice. Results showed that honey promoted the conversion of highly toxic DDAs to less toxic MDAs and prevented MDAs from hydrolyzing into NDAs. Honey-boiled CW formed approximately 250 nm supramolecular aggregates that encapsulated MDAs, inhibiting their conversion to NDAs. These encapsulated MDAs acted as a stable delivery system with higher bioavailability than free benzoylmesaconine. Subsequent mouse experiments confirmed that honey-boiled CW significantly increased the LD₅₀ of CW while reducing hepatotoxicity and nephrotoxicity. Additionally, honey-boiled CW significantly improved cell safety and enhanced anti-inflammatory and analgesic effects. Our findings reveal that honey-boiled CW exhibits a potent detoxification mechanism by influencing alkaloid transformation and facilitating the formation of supramolecular aggregates. This study lays the groundwork for developing detoxification or synergistic strategies within honey-boiled TCM.

Prostate cancer is the most prevalent malignant tumor among men, ranking first in incidence and second in mortality globally. Novel hormone therapies (NHT) targeting the androgen receptor (AR) pathway have become the standard of care for metastatic prostate cancer. This review offers a comprehensive overview of NHT, including abiraterone, enzalutamide, apalutamide, darolutamide, and rezvilutamide, which have demonstrated efficacy in delaying disease progression and improving patient survival and quality of life. Nevertheless, resistance to NHT remains a critical challenge. The mechanisms underlying resistance are complex, involving AR gene amplification, mutations, splice variants, increased intratumoral androgens, and AR-independent pathways such as the glucocorticoid receptor, neuroendocrine differentiation, DNA repair defects, autophagy, immune evasion, and activation of alternative signaling pathways. This review discusses these resistance mechanisms and examines strategies to counteract them, including sequential treatment with novel AR-targeted drugs, chemotherapy, poly ADP-ribose polymerase inhibitors, radionuclide therapy, bipolar androgen therapy, and approaches targeting specific resistance pathways. Future research should prioritize elucidating the molecular basis of NHT resistance, optimizing existing therapeutic strategies, and developing more effective combination regimens. Additionally, advanced sequencing technologies and resistance research models should be leveraged to identify novel therapeutic targets and improve drug delivery efficiencies. These advancements hold the potential to overcome NHT resistance and significantly enhance the management and prognosis of patients with advanced prostate cancer.

ObjectiveTo analyze the distribution characteristics of traditional Chinese medicine （TCM） syndrome elements in different risk populations of heart failure complicated with type 2 diabetes. MethodsClinical data of 675 type 2 diabetes patients were retrospectively collected. Lasso-multivariate Logistic regression was used to construct a clinical prediction nomogram model. Based on this， 441 non-heart failure patients were divided into a low-risk group （325 cases） and a high-risk group （116 cases） according to the median risk score of heart failure complicated with type 2 diabetes. TCM diagnostic information （four diagnostic methods） was collected for both groups， and factor analysis was applied to summarize the distribution of TCM syndrome elements in different risk populations. ResultsLasso-multivariate Logistic regression analysis identified age， disease duration， coronary heart disease， old myocardial infarction， arrhythmia， absolute neutrophil count， activated partial thromboplastin time， and α-hydroxybutyrate dehydrogenase as independent risk factors for heart failure complicated with type 2 diabetes. These were used as final predictive factors to construct the nomogram model. Model validation results showed that the area under the curve （AUC） of the receiver operating characteristic （ROC） curve for the modeling group and validation group were 0.934 and 0.935， respectively. The Hosmer-Lemeshow test （modeling group P = 0.996， validation group P = 0.121） indicated good model discrimination. Decision curve analysis showed that the curves for All and None crossed in the upper right corner， indicating high clinical utility. The low-risk and high-risk groups each obtained 14 common factors. Preliminary analysis revealed that the main disease elements in the low-risk group were qi deficiency （175 cases， 53.85%）， dampness （118 cases， 36.31%）， and heat （118 cases， 36.31%）， with the primary locations in the spleen （125 cases， 38.46%） and lungs （99 cases， 30.46%）. In the high-risk group， the main disease elements were yang deficiency （73 cases， 62.93%）， blood stasis （68 cases， 58.62%）， and heat （49 cases， 42.24%）， with the primary locations in the kidney （84 cases， 72.41%） and heart （70 cases， 60.34%）. ConclusionThe overall disease characteristics in different risk populations of type 2 diabetes patients with heart failure are a combination of deficiency and excess， with deficiency being predominant. Deficiency and heat are present throughout. The low-risk population mainly shows qi deficiency with dampness and heat， related to the spleen and lungs. The high-risk population shows yang deficiency with blood stasis and heat， related to the kidneys and heart.

ObjectiveTo observe the effects of Hei Xiaoyaosan on the learning and memory abilities of Alzheimer's disease model mice （APP/PS1 mice）， and to explore its mechanism through the inflammatory cascade mediated by nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing 3 （NLRP3）/cysteine aspartate-specific protease （Caspase-1）/gasdermin D （GSDMD） signaling pathway. MethodsSPF-grade 4-month-old APP/PS1 mice were randomly divided into the model group， MCC950 group， and Hei Xiaoyaosan high-， medium-， and low-dose groups. C57BL/6J mice were used as the blank group. After 7 days of adaptive feeding， mice in each group were intervened. The Hei Xiaoyaosan high-， medium-， and low-dose groups were given corresponding doses by gavage （25.79， 12.90， 6.45 g·kg^-1·d^-1）， the MCC950 group was intraperitoneally injected with 10 mg·kg^-1·2 d^-1， and the blank group received the same volume of physiological saline by gavage. After 90 days of intervention， the learning and memory abilities were assessed using the Y maze and Morris water maze tests. The structural changes of hippocampal neurons were observed by hematoxylin-eosin （HE） staining. The expression of amyloid precursor protein （APP） in the hippocampal CA3 region was detected by immunohistochemistry. Enzyme-linked immunosorbent assay （ELISA） was used to measure the levels of interleukin （IL）-10， IL-18， and IL-1β in the hippocampus. Western blot was applied to detect the protein expression of NLRP3， Caspase-1， GSDMD， and GSDMD-N in the hippocampus. Immunofluorescence was used to detect the co-localization of GSDMD-N and ionized calcium-binding adapter molecule-1 （Iba-1） in the hippocampus. Results① In the Y maze test， compared with the blank group， the spontaneous alternation rate of the model group was significantly reduced （P<0.01）. Compared with the model group， the spontaneous alternation rate in the Hei Xiaoyaosan high- and low-dose groups was significantly increased （P<0.01）. ② In the Morris water maze test， during the 1-4 days of the location navigation test， the escape latency time of mice decreased with the extension of training time. On day 4， compared with the blank group， the model group showed a significantly increased escape latency （P<0.05）. Compared with the model group， the MCC950 group and the Hei Xiaoyaosan low-dose group showed significantly reduced escape latency （P<0.05）. In the spatial exploration experiment， compared with the blank group， the number of platform crossings in the model group was significantly reduced （P<0.01）. Compared with the model group， the Hei Xiaoyaosan low-dose group showed significantly increased platform crossings （P<0.05）. ③ HE staining showed that， compared with the blank group， the hippocampal CA3 cells of the model group were damaged， arranged loosely and irregularly， swollen， with unclear boundaries， and the nuclei were pyknotic and deeply stained. MCC950 and all doses of Hei Xiaoyaosan improved the hippocampal CA3 cell damage in APP/PS1 mice to varying degrees. ④ Immunohistochemical results indicated that， compared with the blank group， the expression of APP in the hippocampal CA3 region was significantly increased in the model group （P<0.01）. MCC950 and all doses of Hei Xiaoyaosan could reduce the expression of APP in the hippocampal CA3 region of APP/PS1 mice （P<0.01）. ⑤ ELISA results showed that the levels of IL-18 and IL-1β in the hippocampus of mice in the model group were significantly increased， and IL-10 levels were significantly reduced （P<0.01）. Compared with the model group， the IL-18 levels in the MCC950 group and the Hei Xiaoyaosan medium- and low-dose groups were significantly reduced （P<0.01）. IL-1β levels in the hippocampus of the MCC950 group and Hei Xiaoyaosan high-， medium-， and low-dose groups were significantly decreased （P<0.01）. The IL-10 levels in the hippocampus of the MCC950 group and the Hei Xiaoyaosan medium- and low-dose groups were increased （P<0.05， P<0.01）. ⑥ Western blot results showed that compared with the blank group， the protein levels of NLRP3， Caspase-1， GSDMD， and GSDMD-N in the hippocampus of the model group were significantly elevated （P<0.01）. Compared with the model group， the content of NLRP3 and Caspase-1 in the hippocampus of the treated groups was decreased （P<0.05， P<0.01）. The content of GSDMD in the hippocampus of the Hei Xiaoyaosan high-， medium-， and low-dose groups was reduced （P<0.05， P<0.01）， and the content of GSDMD-N in the hippocampus of the Hei Xiaoyaosan medium- and low-dose groups was decreased （P<0.05， P<0.01）. ⑦ Immunofluorescence results showed that， compared with the blank group， the co-expression of GSDMD-N and Iba-1 in the hippocampus of the model group was significantly increased （P<0.01）. Compared with the model group， the co-expression of GSDMD-N and Iba-1 in the treated groups was significantly reduced （P<0.01）. ConclusionHei Xiaoyaosan may regulate the NLRP3/Caspase-1/GSDMD signaling pathway to affect the release of inflammatory factors， alleviate neuroinflammation，improve hippocampal histopathological changes，and improve learning and memory deficits，thus providing potential therapeutic benefits for Alzheimer's disease.

Cerebrovascular diseases, characterized by high incidence, disability, and mortality rates, have emerged as a leading global cause of death and long-term disability. Organoid technology, a three-dimensional in vitro culture system derived from stem cells or tissue cells, enables the simulation of organ development, physiological processes, and pathological mechanisms, demonstrating significant potential in cerebrovascular disease research and therapeutic development. This review summarizes recent advances in organoid applications for cerebrovascular diseases, with a focus on strategies for constructing vascularized cerebral organoids, including in vivo transplantation, in vitro culture systems, and bioengineering approaches. Studies reveal that these models not only recapitulate neurovascular unit interactions but also serve as powerful platforms for drug screening and mechanistic investigations, offering novel therapeutic strategies for cerebrovascular disorders. Current challenges include insufficient vascularization efficiency and limited integration capacity with host tissues. Future integration of gene editing, microfluidic chips, and high-throughput 3D bioprinting technologies is expected to enhance the functionality and clinical translatability of vascularized cerebral organoids, thereby advancing personalized medicine and precision healthcare.

Objective To compare the mid- and long-term clinical results of mitral valve plasty (MVP) and mitral valve replacement (MVR) in the treatment of functional mitral regurgitation (FMR). Methods Patients with FMR who underwent surgical treatment in the Department of Cardiovascular Surgery of the General Hospital of Northern Theater Command from 2012 to 2021 were collected. The patients who underwent MVP were divided into a MVP group, and those who underwent MVR into a MVR group. The clinical data and mid-term follow-up efficacy of two groups were compared. Results Finally 236 patients were included. There were 100 patients in the MVP group, including 53 males and 47 females, with an average age of (61.80±8.03) years. There were 136 patients in the MVR group, including 72 males and 64 females, with an average age of (61.29±8.97) years. There was no statistical difference in baseline data between the two groups (P＞0.05). There was no statistical difference between the two groups in the extracorporeal circulation time, aortic occlusion time, postoperative hospital and ICU stay, intraoperative blood loss, or hospitalization death (P＞0.05), but the time of mechanical ventilation in the MVP group was significantly shorter than that in the MVR group (P=0.022). The total follow-up rate was 100.0%, the longest follow-up was 10 years, and the average follow-up time was (3.60±2.55) years. There were statistical differences in the left atrial diameter, left ventricular end-diastolic diameter, left ventricular end-systolic diameter and cardiac function between the two groups compared with those before surgery (P<0.05). The postoperative left ventricular ejection fraction in the MVP group was statistically higher than that before surgery (P=0.002), but there was no statistical difference in the MVR group before and after surgery (P=0.658). The left atrial diameter in the MVP group was reduced compared with the MVR group (P=0.026). The recurrence rate of mitral regurgitation in the MVP group was higher than that in the MVR group, and the difference was statistically significant (10.0% vs. 1.5%, P=0.003). There were 14 deaths in the MVP group and 19 in the MVR group. The cumulative survival rate (P=0.605) and cardiovascular events-free survival rate (P=0.875) were not statistically significant between the two groups by Kaplan-Meier survival analysis. Conclusion The safety, and mid- and long-term clinical efficacy of MVP in the treatment of FMR patients are better than MVR, and the left atrial and left ventricular diameters are statistically reduced, and cardiac function is statistically improved. However, the surgeon needs to be well aware of the indications for the MVP procedure to reduce the rate of mitral regurgitation recurrence.

BACKGROUND: Lung cancer is one of the most common malignant tumors worldwide and a major cause of cancer-related deaths. Early-stage lung cancer is often manifested as pulmonary nodules, and accurate assessment of the malignancy risk is crucial for prolonging survival and avoiding overtreatment. This study aims to construct a model based on image feature parameters automatically extracted by artificial intelligence (AI) to evaluate its effectiveness in predicting the malignancy of part-solid nodule (PSN). METHODS: This retrospective study analyzed 229 PSN from 222 patients who underwent pulmonary nodule resection at Lanzhou University Second Hospital between October 2020 and February 2025. According to pathological results, 45 cases of benign lesions and precursor glandular lesion were categorized into the non-malignant group, and 184 cases of pulmonary malignancies were categorized into the malignant group. All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. Univariate analysis was used to screen significant variables; variance inflation factor (VIF) was calculated to exclude highly collinear variables, and LASSO regression was further applied to identify key features. Multivariate Logistic regression was used to determine independent risk factors. Based on the selected variables, five models were constructed: Logistic regression, random forest, XGBoost, LightGBM, and support vector machine (SVM). Receiver operating characteristic (ROC) curves were used to assess the performance of the models. RESULTS: The independent risk factors for the malignancy of PSN include roughness (ngtdm), dependence variance (gldm), and short run low gray-level emphasis (glrlm). Logistic regression achieved area under the curves ( AUCs) of 0.86 and 0.89 in the training and testing sets, respectively, showing good performance. XGBoost had AUCs of 0.78 and 0.77, respectively, demonstrating relatively balanced performance, but with lower accuracy. SVM showed an AUC of 0.93 in the training set, which decreased to 0.80 in the testing set, indicating overfitting. LightGBM performed excellently in the training set with an AUC of 0.94, but its performance declined in the testing set, with an AUC of 0.88. In contrast, random forest demonstrated stable performance in both the training and testing sets, with AUCs of 0.89 and 0.91, respectively, exhibiting high stability and excellent generalizability. CONCLUSIONS The random forest model constructed based on independent risk factors demonstrated the best performance in predicting the malignancy of PSN and could provide effective auxiliary predictions for clinicians, supporting individualized treatment decisions.
.
Humans ; Male ; Female ; Lung Neoplasms/pathology* ; Middle Aged ; Retrospective Studies ; Artificial Intelligence ; Aged ; Tomography, X-Ray Computed ; Adult ; Solitary Pulmonary Nodule/diagnostic imaging* ; ROC Curve

Cancer is characterized by abnormal cell proliferation. Cyclins and cyclin-dependent kinases (CDKs) have been recognized as essential regulators of the intricate cell cycle, orchestrating DNA replication and transcription, RNA splicing, and protein synthesis. Dysregulation of the CDK pathway is prevalent in the development and progression of human cancers, rendering cyclins and CDKs attractive therapeutic targets. Several CDK4/6 inhibitors have demonstrated promising anti-cancer efficacy and have been successfully translated into clinical use, fueling the development of CDK-targeted therapies. With this enthusiasm for finding novel CDK-targeting anti-cancer agents, there have also been exciting advances in the field of targeted protein degradation through innovative strategies, such as using proteolysis-targeting chimera, heat shock protein 90 (HSP90)‍-mediated targeting chimera, hydrophobic tag-based protein degradation, and molecular glue. With a focus on the translational potential of cyclin- and CDK-targeting strategies in cancer, this review presents the fundamental roles of cyclins and CDKs in cancer. Furthermore, it summarizes current strategies for the proteasome-dependent targeted degradation of cyclins and CDKs, detailing the underlying mechanisms of action for each approach. A comprehensive overview of the structure and activity of existing CDK degraders is also provided. By examining the structure‍‒‍activity relationships, target profiles, and biological effects of reported cyclin/CDK degraders, this review provides a valuable reference for both CDK pathway-targeted biomedical research and cancer therapeutics.
Humans ; Neoplasms/metabolism* ; Cyclin-Dependent Kinases/antagonists & inhibitors* ; Cyclins/metabolism* ; Proteolysis ; Antineoplastic Agents/pharmacology* ; Molecular Targeted Therapy ; Proteasome Endopeptidase Complex/metabolism* ; Animals

Bone repair remains an important target in tissue engineering, making the development of bioactive scaffolds for effective bone defect repair a critical objective. In this study, β-tricalcium phosphate (β-TCP) scaffolds incorporated with processed pyritum decoction (PPD) were fabricated using three-dimensional (3D) printing-assisted freeze-casting. The produced composite scaffolds were evaluated for their mechanical strength, physicochemical properties, biocompatibility, in vitro pro-angiogenic activity, and in vivo efficacy in repairing rabbit femoral defects. They not only demonstrated excellent physicochemical properties, enhanced mechanical strength, and good biosafety but also significantly promoted the proliferation, migration, and aggregation of pro-angiogenic human umbilical vein endothelial cells (HUVECs). In vivo studies revealed that all scaffold groups facilitated osteogenesis at the bone defect site, with the β-TCP scaffolds loaded with PPD markedly enhancing the expression of neurogenic locus Notch homolog protein 1 (Notch1), vascular endothelial growth factor (VEGF), bone morphogenetic protein-2 (BMP-2), and osteopontin (OPN). Overall, the scaffolds developed in this study exhibited strong angiogenic and osteogenic capabilities both in vitro and in vivo. The incorporation of PPD notably promoted the angiogenic-osteogenic coupling, thereby accelerating bone repair, which suggests that PPD is a promising material for bone repair and that the PPD/β-TCP scaffolds hold great potential as a bone graft alternative.
Calcium Phosphates/chemistry* ; Animals ; Bone Regeneration ; Rabbits ; Tissue Scaffolds ; Printing, Three-Dimensional ; Humans ; Human Umbilical Vein Endothelial Cells ; Neovascularization, Physiologic ; Osteogenesis ; Tissue Engineering/methods* ; Biomimetic Materials ; Cell Proliferation ; Angiogenesis