BACKGROUND:Epidemiological studies indicate that individuals with neurodegenerative diseases exhibit a comparatively lower risk of developing the majority of cancers.Although the precise mechanisms underlying this inverse correlation remain unclear,it is noteworthy that aberrant glucose metabolism,a pathological factor common to both conditions,may significantly contribute to this association.OBJECTIVE:To review the potential relationship between cancers and neurodegenerative diseases in glucose metabolism.METHODS:PubMed was searched for relevant literature using the search terms of"cancer,neurodegenerative diseases,Alzheimer's disease,Parkinson's disease,metabolic reprogramming,glucose metabolism,aerobic glycolysis,neuroprotection,aging,"and 136 articles were finally included for analysis.RESULTS AND CONCLUSION:Cancer and neurodegenerative diseases exhibit a profound pathological correlation at the level of glucose metabolism imbalance associated with aging.Cancer cells promote uncontrolled proliferation,invasion,and metastasis through the persistent activation of aerobic glycolysis,whereas neurodegenerative diseases are characterized by a reduction in aerobic glycolysis.Restoring aerobic glycolysis may confer neuroprotective effects and delay disease progression.The key nodes of glucose metabolism demonstrate a bidirectional regulatory pattern:metabolic regulators,which are significantly upregulated or aberrantly activated in cancer,are inhibited or functionally inactivated in neurodegenerative diseases.Mitochondria play a crucial role in mediating the aging process through the regulation of reactive oxygen species homeostasis and mitochondrial autophagy.They establish regulatory networks that connect cancer and neurodegenerative diseases,and maintaining their functional homeostasis is of paramount importance for disease prevention and treatment.

BACKGROUND:Epidemiological studies indicate that individuals with neurodegenerative diseases exhibit a comparatively lower risk of developing the majority of cancers.Although the precise mechanisms underlying this inverse correlation remain unclear,it is noteworthy that aberrant glucose metabolism,a pathological factor common to both conditions,may significantly contribute to this association.OBJECTIVE:To review the potential relationship between cancers and neurodegenerative diseases in glucose metabolism.METHODS:PubMed was searched for relevant literature using the search terms of"cancer,neurodegenerative diseases,Alzheimer's disease,Parkinson's disease,metabolic reprogramming,glucose metabolism,aerobic glycolysis,neuroprotection,aging,"and 136 articles were finally included for analysis.RESULTS AND CONCLUSION:Cancer and neurodegenerative diseases exhibit a profound pathological correlation at the level of glucose metabolism imbalance associated with aging.Cancer cells promote uncontrolled proliferation,invasion,and metastasis through the persistent activation of aerobic glycolysis,whereas neurodegenerative diseases are characterized by a reduction in aerobic glycolysis.Restoring aerobic glycolysis may confer neuroprotective effects and delay disease progression.The key nodes of glucose metabolism demonstrate a bidirectional regulatory pattern:metabolic regulators,which are significantly upregulated or aberrantly activated in cancer,are inhibited or functionally inactivated in neurodegenerative diseases.Mitochondria play a crucial role in mediating the aging process through the regulation of reactive oxygen species homeostasis and mitochondrial autophagy.They establish regulatory networks that connect cancer and neurodegenerative diseases,and maintaining their functional homeostasis is of paramount importance for disease prevention and treatment.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

AIM: To evaluate the efficacy and safety of 3% diquafosol sodium eye drops in children wearing orthokeratology lenses and with dry eye disease(DED)or at risk of DED.METHODS: Randomized controlled trials. Children with DED or at risk of DED were randomly assigned in a 1:1 ratio to receive either 3% diquafosol sodium eye drops 6 times daily or a blank control at Chongqing Aier Children's Eye Hospital from November 2023 to November 2024. The primary endpoint was the change in the Dry Eye Questionnaire-5(DEQ-5)score from baseline at 12 wk. Secondary assessments included non-invasive breakup time(NIBUT), tear meniscus height, Schirmer's test, corneal fluorescein staining score, and axial length.RESULTS: A total of 80 participants(80 eyes)were enrolled(40 in each group), the average age of the participants was 11.11±1.88 years, with 43 females(54%)and 37 males(46%), and all completed the trial. After 12 wk, the DEQ-5 scores for the diquafosol sodium group and the blank control group were 1.88±2.02 and 2.88±2.79, respectively(P=0.079). The diquafosol sodium group demonstrated a significant improvement in DEQ-5 dryness symptom scores(-0.33±0.66 vs. 0.05±0.81, P=0.023)and NIBUT(6.18±3.73 vs. -1.09±4.40 s, P<0.001)at 12 wk. Additionally, the diquafosol sodium group showed no axial length elongation, in contrast to the blank control group, which exhibited elongation(0.00±0.08 vs. 0.05±0.10 mm, P=0.013). No other significant differences were found in the secondary endpoints. No adverse events occurred during the trial.CONCLUSION: Although no statistically significant improvements were noted in the overall DEQ-5 scores, the 3% diquafosol sodium eye drops significantly improved dryness symptoms and NIBUT when compared to the blank control group.

BackgroundIndividuals with schizophrenia are prone to higher rates of hospital readmission， presenting significant clinical challenges and imposing considerable social burdens within the mental health domain. In recent years， various risk prediction models have been developed to forecast readmission in patients with schizophrenia and support clinical decision-making， but their predictive performance and clinical applicability require comprehensive evaluation. ObjectiveTo systematically evaluate the risk prediction models for readmission in patients with schizophrenia， so as to provide insights for the development of high-performance and highly applicable readmission risk prediction models for patients with schizophrenia. MethodsOn July 5， 2025， a systematic literature search was conducted across multiple electronic databases， including PubMed， Embase， Cochrane Library， Web of Science， CINAHL， CNKI， China Biomedical Literature Database， Wanfang Database， and VIP Database， to identify risk prediction models for readmission in patients with schizophrenia. The search period was from the establishment of the databases to July 1， 2025. Two researchers independently performed literature screening， data extraction， risk of bias assessment， and applicability assessment. ResultsA total of 9 studies were included in this review， encompassing 18 risk prediction models for readmission in patients with schizophrenia. Among them， 4 models reported the area under the receiver operating characteristic （ROC） curve （AUC）， ranging from 0.734 to 0.820， 16 models provided AUC values of 0.642–0.879 for internal validation， and 1 model demonstrated an AUC of 0.841 for external validation. Key predictors included disease duration and the concomitant therapy of antipsychotic medications. The risk of bias was assessed as "high" in all included studies. ConclusionThe development of risk prediction models for readmission in patients with schizophrenia remains in an exploratory stage. Although the model exhibits favorable predictive performance， it is associated with a high risk of bias and insufficient performance evaluation.

Atherosclerosis （AS） is the main pathological basis of cardiovascular diseases， and its occurrence and development are closely related to epigenetic regulation. Histone modification， as the core mechanism of epigenetic regulation， plays a crucial role in the occurrence and development of AS by dynamically regulating chromatin structure and gene expression. In recent years， traditional Chinese medicine （TCM） and its active components have shown unique advantages and potential in regulating histone modification for the prevention and treatment of AS. This article systematically reviews the mechanisms of histone acetylation， methylation， lactylation， etc. in the pathological process of AS and summarizes the latest research progress in the intervention of AS by the active components and compound prescriptions of TCM through regulating histone modification. Studies have indicated that TCM and its compound prescriptions regulate the activities of histone modification enzymes via multiple targets， showing unique advantages in influencing lipid metabolism and inflammatory response， as well as stabilizing vulnerable plaques and endothelial function. The active components of TCM directly target the activities or expression of histone modification enzymes such as histone acetyltransferases （HATs）， histone deacetylases （HDACs）， histone lysine methyltransferases （KMTs）， and histone lysine demethylases （KDMs）， thereby causing changes in histone modification and ultimately affecting gene expression and pathological phenotype in AS. However， current research still has problems such as insufficient in-depth basic research， unclear intervention effects and mechanisms of AS dynamics， relatively isolated studies on various factors of epigenetic modification， and unclear establishment of quality control standards for TCM compound prescriptions based on epigenetic regulation. In the future， in-depth research is still needed， and the research results should be translated into clinical applications. This article systematically clarifies the key role and mechanism of TCM in regulating the pathological process of AS through epigenetic intervention， providing new ideas for the modernization of TCM and precise prevention and treatment of AS.

Atherosclerosis （AS） is the main pathological basis of cardiovascular diseases， and its occurrence and development are closely related to epigenetic regulation. Histone modification， as the core mechanism of epigenetic regulation， plays a crucial role in the occurrence and development of AS by dynamically regulating chromatin structure and gene expression. In recent years， traditional Chinese medicine （TCM） and its active components have shown unique advantages and potential in regulating histone modification for the prevention and treatment of AS. This article systematically reviews the mechanisms of histone acetylation， methylation， lactylation， etc. in the pathological process of AS and summarizes the latest research progress in the intervention of AS by the active components and compound prescriptions of TCM through regulating histone modification. Studies have indicated that TCM and its compound prescriptions regulate the activities of histone modification enzymes via multiple targets， showing unique advantages in influencing lipid metabolism and inflammatory response， as well as stabilizing vulnerable plaques and endothelial function. The active components of TCM directly target the activities or expression of histone modification enzymes such as histone acetyltransferases （HATs）， histone deacetylases （HDACs）， histone lysine methyltransferases （KMTs）， and histone lysine demethylases （KDMs）， thereby causing changes in histone modification and ultimately affecting gene expression and pathological phenotype in AS. However， current research still has problems such as insufficient in-depth basic research， unclear intervention effects and mechanisms of AS dynamics， relatively isolated studies on various factors of epigenetic modification， and unclear establishment of quality control standards for TCM compound prescriptions based on epigenetic regulation. In the future， in-depth research is still needed， and the research results should be translated into clinical applications. This article systematically clarifies the key role and mechanism of TCM in regulating the pathological process of AS through epigenetic intervention， providing new ideas for the modernization of TCM and precise prevention and treatment of AS.

Objective To explore the clinical values of non-invasive myocardial work (MW) and tissue motion annular displacement (TMAD) in evaluation of anthracycline therapy-related cardiac dysfunction in patients with non-Hodgkin lymphoma. Methods A total of 62 patients with non-Hodgkin lymphoma who received standardized chemotherapy based on doxorubicin. Two and three dimensional transthoracic echocardiography, along with two dimensional speckle tracking echocardiography, were performed one day before chemotherapy and at 3, 6, and 9 months after chemotherapy to assess left ventricular ejection fraction, global longitudinal strain (GLS), MW parameters, and TMAD. Logistic regression analysis was used to evaluate the risk factors for cancer therapy-related cardiac dysfunction (CTRCD). The receiver operating characteristic curve was used to assess the diagnostic values of MW- and TMAD-related parameters for CTRCD. Results Compared to baseline, GLS, global work index (GWI), global constructive work (GCW), global work efficiency (GWE), TMAD at midpoint (TMADmid), and TMADmid percentage of left ventricular long-axis diameter (TMADmid%) decreased at 3 months after chemotherapy, while global wasted work (GWW) increased at 6 months after chemotherapy (P＜0.05). Logistic regression analysis showed that the relative reduction in GLS and TMADmid% at 3 months after chemotherapy were independent predictors for CTRCD （P＜0.05), while MW parameters were not independent predictors for CTRCD. GLS reduction≥10.3% and TMADmid% reduction≥15.8% at 3 months after chemotherapy predicted CTRCD with 0.866 and 0.824 of area under the curve (AUC), 92% and 75% of sensitivity, and 74% and 80% of specificity, respectively. AUC of combination of two indexes improved to 0.905, with 75% of sensitivity and 90% of specificity. Conclusions In non-Hodgkin lymphoma patients, the combination of GLS and TMADmid% is helpful of predicting CTRCD early, TMAD may be a novel diagnostic index for CTRCD, and GLS has superior predictive performance than MW for CTRCD.