ObjectiveTo explore the molecular mechanism of aerobic exercise to improve hippocampal neuronal degeneration by regulating tryptophan metabolic pathway. Methods60 SPF-grade C57BL/6J male mice were divided into a young group (2 months old, n=30) and a senile group (12 months old, n=30), and each group was further divided into a control group (C/A group, n=15) and an exercise group (CE/AE group, n=15). An aerobic exercise program was used for 8 weeks. Learning memory ability was assessed by Y-maze, and anxiety-depression-like behavior was detected by absent field experiment. Hippocampal Trp levels were measured by GC-MS. Nissl staining was used to observe the number and morphology of hippocampal neurons, and electron microscopy was used to detect synaptic ultrastructure. ELISA was used to detect the levels of hippocampal Trp,5-HT, Kyn, KATs, KYNA, KMO, and QUIN; Western blot was used to analyze the activities of TPH2, IDO1, and TDO enzymes. ResultsGroup A mice showed significant decrease in learning and memory ability (P<0.05) and increase in anxiety and depressive behaviors (P<0.05); all of AE group showed significant improvement (P<0.05). Hippocampal Trp levels decreased in group A (P<0.05) and increased in AE group (P<0.05). Nidus vesicles were reduced and synaptic structures were degraded in group A (P<0.05), and both were significantly improved in group AE (P<0.05). The levels of Trp, 5-HT, KATs, and KYNA were decreased (P<0.05) and the levels of Kyn, KMO, and QUIN were increased (P<0.05) in group A. The activity of TPH2 was decreased (P<0.05), and the activities of IDO1 and TDO were increased (P<0.05). The AE group showed the opposite trend. ConclusionThe aging process significantly reduces the learning memory ability and increases the anxiety-depression-like behavior of mice, and leads to the reduction of the number of nidus vesicles and degenerative changes of synaptic structure in the hippocampus, whereas aerobic exercise not only effectively enhances the spatial learning memory ability and alleviates the anxiety-depression-like behavior of aging mice, but also improves the morphology and structure of neurons in hippocampal area, which may be achieved by the mechanism of regulating the tryptophan metabolic pathway.

Objective To investigate the current status of symptom burden and psychological distress among lung cancer patients in the diagnostic phase, and to explore the chain mediating role of social support and resilience between symptom burden and psychological distress. Methods The patients with lung cancer in the diagnostic phase who were treated in the Department of Thoracic Surgery of the Second Xiangya Hospital of Central South University from October 2022 to June 2023 were investigated by a general information questionnaire using the MD Anderson Symptom Inventory, the Social Support Rating Scale, the Connor-Davidson Resilience Scale, and the Distress Thermometer. The chain mediating role of social support and resilience between symptom burden and psychological distress was analyzed. Results A total of 413 lung cancer patients were enrolled, including 173 males and 240 females, aged (54.69±10.82) years. The detection rate of psychological distress among lung cancer patients in the diagnostic phase was 48.18%, and the average score was (3.84±2.50) points. Psychological distress was positively correlated with symptom burden (P<0.01), and negatively correlated with social support and resilience (P<0.01). The mediating effect of resilience between symptom burden and psychological distress was significant. The chain mediating effect of social support and resilience between symptom burden and psychological distress was also significant. Conclusion Lung cancer patients in the diagnostic phase have a high detection rate of psychological distress. Symptom burden can directly impact psychological distress, and can affect psychological distress through the indirect path of resilience as well as the chain mediating path between social support and resilience among lung cancer patients in the diagnostic phase.

RNA-binding protein human antigen R(HuR)is a protein product of the embryonic lethal abnormal vision gene(ELAVL).It is widely expressed in human cells and primarily regulates mRNA stability through post-transcriptional mecha-nisms,particularly by binding to AU-enriched elements(AR-Es).Recent studies have indicated that HuR interacts with non-coding RNAs to participate in the regulation of gene expression,including long non-coding RNAs,circular RNAs,microRNAs,and vault RNAs.The interactions between HuR and these ncR-NAs play a crucial role in the occurrence and development of va-rious diseases,including tumors.Since there are already reviews summarizing the research on tumors,this review mainly focuses on summarizing the role of HuR-ncRNA interactions in diseases other than tumors.

Objective To observe the efficacy of self-guided attention network for detecting responsible lesions related to cerebral palsy(CP)in children with periventricular white matter injury(PVWMI).Methods Totally 383 children with PVWMI were retrospectively enrolled and divided into CP group(n=243)and non-CP group(n=140),while 214 children without obvious brain abnormality on brain MRI were taken as control group.ROI of 4 key anatomical structures related to CP,i.e.centrum semiovale,posterior limb of internal capsule,cerebral peduncle and thalamus were delineated on T1WI,while responsible lesions related to CP within the key anatomical structures were labeled on T2WI,and the images were then registrated and used as input of the networks.ResNet34 network was adopted combined with attention and self-guided networks to train the network for detecting responsible lesions related to CP in children with PVWMI,and their efficacies were evaluated.The optimal network was screened,and its efficacy for segmenting the key anatomical structures was evaluated.Results Self-guided attention network was the optimal network,its area under the curve(AUC)for detecting lesions was 0.794-0.914,and the Dice similarity coefficient for segmenting the key anatomical structures was 0.702-0.764.Conclusion Self-guided attention network could be used for preliminarily detecting responsible lesions related to CP in children with PVWMI.

Aim To explore the potential mechanisms underlying therapeutic effects of cordycepin in asthma by utilizing network pharmacology,molecular docking,and in vitro cellular validation.Methods The thera-peutic targets associated with asthma and the drug tar-gets of cordycepin were systematically identified through comprehensive database searches.An overlap analysis of the two gene sets was performed,followed by the construction of a protein-protein interaction(PPI)network and topological analysis to identify the core targets.The core targets were subjected to Kyoto Ency-clopedia of Genes and Genomes(KEGG)pathway a-nalysis and Gene Ontology(GO)enrichment analysis,and a drug-target-pathway network was constructed.To validate the interaction between cordycepin and core targets,molecular docking and molecular dynamics sim-ulations were conducted.Subsequently,the pharmaco-logical effects and underlying mechanisms of cordyce-pin were validated in vitro using Beas-2B cells,emplo-ying Cell Counting Kit-8(CCK-8)assay and quantita-tive real-time reverse transcription PCR(RT-qPCR).Results A total of 438 potential targets of cordycepin were identified,113 of which overlapped with asthma-related therapeutic targets.Topological analysis based on the PPI network revealed 22 core targets.Using KEGG enrichment analysis,165 significantly enriched pathways were identified,including the TNF and HIF-1 signaling pathways.Molecular docking analysis re-vealed high binding affinities between cordycepin and select core targets,which further corroborated by mo-lecular dynamics simulations.In vitro experiments showed that after cordycepin pretreatment,the upregu-lation of MAPK1,HIF1A,MTOR,MYC,IL10,and JUN mRNA was significantly rescued in HDM-stimulated Beas-2B cells.Conclusions Cordycepin exerts anti-asthmatic effects by targeting MAPK1 and other key molecules,thereby providing a scientific foundation for its further development and clinical application.

Aim To explore the potential mechanisms underlying therapeutic effects of cordycepin in asthma by utilizing network pharmacology,molecular docking,and in vitro cellular validation.Methods The thera-peutic targets associated with asthma and the drug tar-gets of cordycepin were systematically identified through comprehensive database searches.An overlap analysis of the two gene sets was performed,followed by the construction of a protein-protein interaction(PPI)network and topological analysis to identify the core targets.The core targets were subjected to Kyoto Ency-clopedia of Genes and Genomes(KEGG)pathway a-nalysis and Gene Ontology(GO)enrichment analysis,and a drug-target-pathway network was constructed.To validate the interaction between cordycepin and core targets,molecular docking and molecular dynamics sim-ulations were conducted.Subsequently,the pharmaco-logical effects and underlying mechanisms of cordyce-pin were validated in vitro using Beas-2B cells,emplo-ying Cell Counting Kit-8(CCK-8)assay and quantita-tive real-time reverse transcription PCR(RT-qPCR).Results A total of 438 potential targets of cordycepin were identified,113 of which overlapped with asthma-related therapeutic targets.Topological analysis based on the PPI network revealed 22 core targets.Using KEGG enrichment analysis,165 significantly enriched pathways were identified,including the TNF and HIF-1 signaling pathways.Molecular docking analysis re-vealed high binding affinities between cordycepin and select core targets,which further corroborated by mo-lecular dynamics simulations.In vitro experiments showed that after cordycepin pretreatment,the upregu-lation of MAPK1,HIF1A,MTOR,MYC,IL10,and JUN mRNA was significantly rescued in HDM-stimulated Beas-2B cells.Conclusions Cordycepin exerts anti-asthmatic effects by targeting MAPK1 and other key molecules,thereby providing a scientific foundation for its further development and clinical application.

Objective To observe the efficacy of self-guided attention network for detecting responsible lesions related to cerebral palsy(CP)in children with periventricular white matter injury(PVWMI).Methods Totally 383 children with PVWMI were retrospectively enrolled and divided into CP group(n=243)and non-CP group(n=140),while 214 children without obvious brain abnormality on brain MRI were taken as control group.ROI of 4 key anatomical structures related to CP,i.e.centrum semiovale,posterior limb of internal capsule,cerebral peduncle and thalamus were delineated on T1WI,while responsible lesions related to CP within the key anatomical structures were labeled on T2WI,and the images were then registrated and used as input of the networks.ResNet34 network was adopted combined with attention and self-guided networks to train the network for detecting responsible lesions related to CP in children with PVWMI,and their efficacies were evaluated.The optimal network was screened,and its efficacy for segmenting the key anatomical structures was evaluated.Results Self-guided attention network was the optimal network,its area under the curve(AUC)for detecting lesions was 0.794-0.914,and the Dice similarity coefficient for segmenting the key anatomical structures was 0.702-0.764.Conclusion Self-guided attention network could be used for preliminarily detecting responsible lesions related to CP in children with PVWMI.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.