Objective To investigate the relationship between cyclin A2 (CCNA2) and the prognosis of colon cancer, and its possible mechanism from the perspective of immune infiltration. Methods We downloaded the transcriptome data of colon cancer patients from The Cancer Genome Atlas database. Clinicopathological feature analysis and survival analysis were performed based on the expression levels of CCNA2. A total of 75 specimens of colon cancer and normal tissues were collected, and the expression level of CCNA2 was analyzed using immunohistochemical methods. Multivariate analysis was conducted to explore its relationship with clinicopathological features. Gene Set Enrichment Analysis (GSEA) was used to assess the potential molecular functions of CCNA2 in colon cancer. CIBERSORT algorithm was applied to calculate the correlation between CCNA2 and immune-cell infiltration in colon cancer. Results Database and immunohistochemical analyses indicated that CCNA2 was expressed at a significantly higher level in colon cancer tissues than normal tissues (P<0.001). The overall survival, disease-specific survival, and progression-free interval were all longer in the group with high CCNA2 expression than the group with low expression (all P<0.05). In tumor tissues, the expression level of CCNA2 decreased with increased pathological and TNM stages (P<0.05). The expression level of CCNA2 in normal tissues was consistently lower than that in colon cancer tissues across all clinical stages (all P<0.001). GSEA suggested that Wnt/β-catenin, KRAS, and other signaling pathways were enriched when CCNA2 was lowly expressed. CIBERSORT analysis revealed an increase in the infiltration of immune cells such as regulatory T cells and macrophages M0 when CCNA2 expression was low. Conclusion CCNA2 is highly expressed in colon cancer and closely associated with grade of pathology and TNM stage. It may recruit regulatory T cells through the KRAS and Wnt/β-catenin pathways, thereby reducing immune-cell infiltration and promoting colon cancer progression, leading to poor prognosis.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Existing studies have underscored the pivotal role of N-acetyltransferase 10 (NAT10) in various cancers. However, the outcomes of protein-protein interactions between NAT10 and its protein partners in head and neck squamous cell carcinoma (HNSCC) remain unexplored. In this study, we identified a significant upregulation of RNA-binding protein with serine-rich domain 1 (RNPS1) in HNSCC, where RNPS1 inhibits the ubiquitination degradation of NAT10 by E3 ubiquitin ligase, zinc finger SWIM domain-containing protein 6 (ZSWIM6), through direct protein interaction, thereby promoting high NAT10 expression in HNSCC. This upregulated NAT10 stability mediates the enhancement of specific tRNA ac⁴C modifications, subsequently boosting the translation process of genes involved in pathways such as IL-6 signaling, IL-8 signaling, and PTEN signaling that play roles in regulating HNSCC malignant progression, ultimately influencing the survival and prognosis of HNSCC patients. Additionally, we pioneered the development of TRMC-seq, leading to the discovery of novel tRNA-ac⁴C modification sites, thereby providing a potent sequencing tool for tRNA-ac⁴C research. Our findings expand the repertoire of tRNA ac⁴C modifications and identify a role of tRNA ac⁴C in the regulation of mRNA translation in HNSCC.
Humans ; DNA-Binding Proteins ; Head and Neck Neoplasms/genetics* ; N-Terminal Acetyltransferases ; RNA, Transfer ; Serine ; Signal Transduction ; Squamous Cell Carcinoma of Head and Neck

ObjectiveTo investigate the effect of kinesin family member 15 （KIF15） on the proliferation of hepatocellular carcinoma （HCC） cells and its mechanism of action. MethodsTCGA and GEPIA datasets were analyzed to determine the expression of KIF15 in HCC and its effect on tumor stage and survival. Quantitative real-time PCR and Western blot were used to measure the expression level of KIF15 in human-derived HCC cell lines （HepG2， Hep3B， MHCC-97H， and LM3） and human normal liver cell line L02 cultured in vitro， and Hep3B and HepG2 were selected for subsequent studies. CCK-8 assay， plate colony formation assay， and EdU staining were performed for Hep3B cells transfected with shRNA-NC or shRNA-KIF15 and HepG2 cells transfected with LV-vector or LV-KIF15 to evaluate the viability and proliferative capacity of these cells. GSEA was used to analyze the potential signaling pathways associated with KIF15 in HCC， and Western blot was used for detection. The independent-samples t test was used for comparison of continuous data between two groups； a one-way analysis of variance was used for comparison between multiple groups， and the least significant difference t-test was used for further comparison between two groups. ResultsThe analysis of TCGA and GEPIA datasets showed that in HCC patients， the expression of KIF15 in HCC tissue was significantly higher than that in normal tissue， and the HCC patients with high KIF15 expression tended to have a poorer prognosis. Compared with sh-NC-Hep3B， sh3-Hep3B showed significant reductions in the mRNA and protein levels of KIF15 （P<0.05）， cell viability， clone formation number， and EdU positive rate （all P<0.05）. Compared with vector-HepG2， LV-KIF15-HepG2 showed significant increases in the mRNA and protein levels of KIF15 （P<0.05）， cell viability， clone formation number， and EdU positive rate （all P<0.05）. Subcutaneous tumor assay showed that compared with sh-NC-Hep3B， sh3-Hep3B showed reductions in tumor volume and tumor weight， as well as a significant reduction in the immunohistochemical score of Ki67 and a significant increase in the immunohistochemical score of TUNEL （P<0.05）. GSEA analysis showed that the PI3K/AKT/mTOR pathway was positively correlated with KIF15 in HCC （NES=1.59， P<0.001）. Western blot showed that LY294002 could inhibit the PI3K/AKT/mTOR pathway upregulated in LV-KIF15-HepG2， and compared with LV-KIF15-HepG2， LY294002+LV-KIF15-HepG2 showed significant reductions in cell viability， clone formation number， and EdU positive rate （all P<0.05）. ConclusionKIF15 enhances the viability and proliferative capacity of HCC cells by upregulating the PI3K/AKT/mTOR signaling pathway.

OBJECTIVE: To explore the mechanism of electroacupuncture (EA) in promoting recovery of the facial function with the involvement of autophagy, glial cell line-derived neurotrophic factor (GDNF), and phosphatidylinositol-3-kinase (PI3K)/mammalian target of rapamycin (mTOR) signaling pathway. METHODS: Seventy-two male Sprague-Dawley rats were randomly allocated into the control, sham-operated, facial nerve injury (FNI), EA, EA+3-methyladenine (3-MA), and EA+GDNF antagonist groups using a random number table, with 12 rats in each group. An FNI rat model was established with facial nerve crushing method. EA intervention was conducted at Dicang (ST 4), Jiache (ST 6), Yifeng (SJ 17), and Hegu (LI 4) acupoints for 2 weeks. The Simone's 10-Point Scale was utilized to monitor the recovery of facial function. The histopathological evaluation of facial nerves was performed using hematoxylin-eosin (HE) staining. The levels of Beclin-1, light chain 3 (LC3), and P62 were detected by immunohistochemistry (IHC), immunofluorescence, and reverse transcription-polymerase chain reaction, respectively. Additionally, IHC was also used to detect the levels of GDNF, Rai, PI3K, and mTOR. RESULTS: The facial functional scores were significantly increased in the EA group than the FNI group (P<0.05 or P<0.01). HE staining showed nerve axons and myelin sheaths, which were destroyed immediately after the injury, were recovered with EA treatment. The expressions of Beclin-1 and LC3 were significantly elevated and the expression of P62 was markedly reduced in FNI rats (P<0.01); however, EA treatment reversed these abnormal changes (P<0.01). Meanwhile, EA stimulation significantly increased the levels of GDNF, Rai, PI3K, and mTOR (P<0.01). After exogenous administration with autophagy inhibitor 3-MA or GDNF antagonist, the repair effect of EA on facial function was attenuated (P<0.05 or P<0.01). CONCLUSIONS EA could promote the recovery of facial function and repair the facial nerve damages in a rat model of FNI. EA may exert this neuroreparative effect through mediating the release of GDNF, activating the PI3K/mTOR signaling pathway, and further regulating the autophagy of facial nerves.
Rats ; Male ; Animals ; Rats, Sprague-Dawley ; Electroacupuncture ; Phosphatidylinositol 3-Kinase/metabolism* ; Facial Nerve Injuries/therapy* ; Phosphatidylinositol 3-Kinases/metabolism* ; Beclin-1 ; Glial Cell Line-Derived Neurotrophic Factor ; Signal Transduction ; TOR Serine-Threonine Kinases/metabolism* ; Autophagy ; Mammals/metabolism*

Existing studies have underscored the pivotal role of N-acetyltransferase 10(NAT10)in various cancers.However,the outcomes of protein-protein interactions between NAT10 and its protein partners in head and neck squamous cell carcinoma(HNSCC)remain unexplored.In this study,we identified a significant upregulation of RNA-binding protein with serine-rich domain 1(RNPS1)in HNSCC,where RNPS1 inhibits the ubiquitination degradation of NAT10 by E3 ubiquitin ligase,zinc finger SWIM domain-containing protein 6(ZSWIM6),through direct protein interaction,thereby promoting high NAT10 expression in HNSCC.This upregulated NAT10 stability mediates the enhancement of specific tRNA ac4C modifications,subsequently boosting the translation process of genes involved in pathways such as IL-6 signaling,IL-8 signaling,and PTEN signaling that play roles in regulating HNSCC malignant progression,ultimately influencing the survival and prognosis of HNSCC patients.Additionally,we pioneered the development of TRMC-seq,leading to the discovery of novel tRNA-ac4C modification sites,thereby providing a potent sequencing tool for tRNA-ac4C research.Our findings expand the repertoire of tRNA ac4C modifications and identify a role of tRNA ac4C in the regulation of mRNA translation in HNSCC.