ObjectiveTo analyze the characteristic expression patterns of six neurotransmitters including 5-hydroxytryptamine （5-HT）， dopamine （DA）， acetylcholine （ACh）， norepinephrine （NE）， inhibitory neurotransmitter （INH）， and excitatory neurotransmitter （EXC） in the whole brain and different brain regions of depression patients by Search of Encephalo Telex （SET）， providing new ideas for the study of heterogeneous etiology of depression. Methods（1） A retrospective study was conducted on supra-slow signals of EEG fluctuations in 1 028 patients with depression. The SET system was used to obtain the expression information of six neurotransmitters in the whole brain and 12 brain regions： left frontal region （F3）， right frontal region （F4）， left central region （C3）， right central region （C4）， left parietal region （P3）， right parietal region （P4）， left occipital region （O1）， right occipital region （O2）， left anterior temporal region （F7）， right anterior temporal region （F8）， left posterior temporal region （T5）， and right posterior temporal region （T6）. The expression information of each neurotransmitter was compared with the normal model， and it was found that single neurotransmitter was in one of three states： increased， decreased， or normal expression. The simultaneous expression states of six neurotransmitters in the brain space were referred to as the expression pattern of multiple neurotransmitters. （2） A MySQL database was established to analyze the actual expression patterns of different neurotransmitters in the whole brain of patients with depression. （3） Factor analysis was conducted to further analyze the characteristic rules of 78 variables of neurotransmitters in the whole brain and 12 brain regions in depression patients. Results（1） The expression of single neurotransmitters in the whole brain and different brain regions of the total depression population showed one of three expression states （increased/decreased/normal）， being normal in the majority. The decreased and increased expression of 5-HT， ACh， DA， INH， EXC， and NE in the whole brain occurred in 6% and 25%， 31% and 17%， 36% and 9%， 15% and 31%， 32% and 14%， and 22% and 22%， respectively. （2） The antagonizing pairs of neurotransmitters （EXC/INH， DA/5-HT， and ACh/NE） showed significant antagonistic relationships in the whole brain and different brain regions， with a strong negative correlation between EXC and INH （P<0.01， |r| values ranging from 0.69 to 0.76）， a strong negative correlation between DA and 5-HT （P<0.01， |r| values ranging from 0.83 to 0.90）， and a moderate negative correlation between ACh and NE （P<0.01， with |r| values ranging from 0.56 to 0.66）. Meanwhile， non-antagonizing pairs of neurotransmitters in the whole brain and different brain regions also showed correlations， with DA/NE （P<0.01， |r| values ranging from 0.38 to 0.46） and NE/EXC （P<0.01， |r| values ranging from 0.56 to 0.61） showing weak and moderate negative correlations， respectively， and DA/EXC showing a weak positive correlation （P<0.01， |r| values ranging from 0.38 to 0.47）. （3） The six neurotransmitters in the 1 028 patients with depression presented a total of 170 expression patterns in the whole brain. The top 30 expression patterns were reported in this paper， with a cumulative rate of 60.60%， including patterns ① INH+/5-HT-/ACh+/DA+/NE-/EXC- （9.05%）， ② INH+/5-HT-/ACh↓/DA+/NE-/EXC- （4.57%）， and ③ INH+/5-HT-/ACh+/DA+/NE↓/EXC- （3.31%）. That is， the proportion of depression patients with normal levels of all the six neurotransmitters was 9.05%， and the patients with at least one neurotransmitter abnormality accounted for 91.95%. （4） The factor analysis extracted 22 common factors from 78 variables in the whole brain and different brain regions. These common factors showed the absolute values of loadings ranging from 0.32 to 0.86 and the eigenvalues （F） ranging from 1.03 to 13.43， with a cumulative contribution rate of 76.82%. The characteristic expression patterns included ① ACh_P3↓/ACh_W↓/ACh_C3↓/ACh_F3↓/ACh_O1↓/ACh_T5↓/ACh_F7↓/NE_P3↑/NE_W↑/NE_C3↑/NE_F3↑/NE_O1↑/NE_T5↑/NE_F7↑ （F=13.43， whole brain）， ② 5-HT_O2↑/DA_O2↓/5-HT_P4↑/DA_P4↓/5-HT_W↑/DA_W↓/5-HT_C4↑/DA_C4↓ （F=5.94）， and ③ EXC_F4↓/DA_F4↓/NE_F4↑/INH_F4↑/5-HT_F4↑/ACh_F4↓ （F=5.33）. ConclusionThe actual 170 expression patterns of 6 neurotransmitters in the whole brain of 1 028 depression patients indicate that depression is a heterogeneous disease with individualized characteristics. The 22 characteristic expression patterns in the whole brain and 12 brain regions verify the pathogenesis hypothesis of multi-neurotransmitters oscillation imbalance in brains of depression patients. In summary， this study provides new guidance for the etiology， diagnosis， and treatment of depression and establishes a methodological foundation for the effectiveness evaluation of individualized treatment of depression by traditional Chinese medicine based on the objective biological markers.

ObjectiveTo analyze the characteristic expression patterns of six neurotransmitters including 5-hydroxytryptamine （5-HT）， dopamine （DA）， acetylcholine （ACh）， norepinephrine （NE）， inhibitory neurotransmitter （INH）， and excitatory neurotransmitter （EXC） in the whole brain and different brain regions of depression patients by Search of Encephalo Telex （SET）， providing new ideas for the study of heterogeneous etiology of depression. Methods（1） A retrospective study was conducted on supra-slow signals of EEG fluctuations in 1 028 patients with depression. The SET system was used to obtain the expression information of six neurotransmitters in the whole brain and 12 brain regions： left frontal region （F3）， right frontal region （F4）， left central region （C3）， right central region （C4）， left parietal region （P3）， right parietal region （P4）， left occipital region （O1）， right occipital region （O2）， left anterior temporal region （F7）， right anterior temporal region （F8）， left posterior temporal region （T5）， and right posterior temporal region （T6）. The expression information of each neurotransmitter was compared with the normal model， and it was found that single neurotransmitter was in one of three states： increased， decreased， or normal expression. The simultaneous expression states of six neurotransmitters in the brain space were referred to as the expression pattern of multiple neurotransmitters. （2） A MySQL database was established to analyze the actual expression patterns of different neurotransmitters in the whole brain of patients with depression. （3） Factor analysis was conducted to further analyze the characteristic rules of 78 variables of neurotransmitters in the whole brain and 12 brain regions in depression patients. Results（1） The expression of single neurotransmitters in the whole brain and different brain regions of the total depression population showed one of three expression states （increased/decreased/normal）， being normal in the majority. The decreased and increased expression of 5-HT， ACh， DA， INH， EXC， and NE in the whole brain occurred in 6% and 25%， 31% and 17%， 36% and 9%， 15% and 31%， 32% and 14%， and 22% and 22%， respectively. （2） The antagonizing pairs of neurotransmitters （EXC/INH， DA/5-HT， and ACh/NE） showed significant antagonistic relationships in the whole brain and different brain regions， with a strong negative correlation between EXC and INH （P<0.01， |r| values ranging from 0.69 to 0.76）， a strong negative correlation between DA and 5-HT （P<0.01， |r| values ranging from 0.83 to 0.90）， and a moderate negative correlation between ACh and NE （P<0.01， with |r| values ranging from 0.56 to 0.66）. Meanwhile， non-antagonizing pairs of neurotransmitters in the whole brain and different brain regions also showed correlations， with DA/NE （P<0.01， |r| values ranging from 0.38 to 0.46） and NE/EXC （P<0.01， |r| values ranging from 0.56 to 0.61） showing weak and moderate negative correlations， respectively， and DA/EXC showing a weak positive correlation （P<0.01， |r| values ranging from 0.38 to 0.47）. （3） The six neurotransmitters in the 1 028 patients with depression presented a total of 170 expression patterns in the whole brain. The top 30 expression patterns were reported in this paper， with a cumulative rate of 60.60%， including patterns ① INH+/5-HT-/ACh+/DA+/NE-/EXC- （9.05%）， ② INH+/5-HT-/ACh↓/DA+/NE-/EXC- （4.57%）， and ③ INH+/5-HT-/ACh+/DA+/NE↓/EXC- （3.31%）. That is， the proportion of depression patients with normal levels of all the six neurotransmitters was 9.05%， and the patients with at least one neurotransmitter abnormality accounted for 91.95%. （4） The factor analysis extracted 22 common factors from 78 variables in the whole brain and different brain regions. These common factors showed the absolute values of loadings ranging from 0.32 to 0.86 and the eigenvalues （F） ranging from 1.03 to 13.43， with a cumulative contribution rate of 76.82%. The characteristic expression patterns included ① ACh_P3↓/ACh_W↓/ACh_C3↓/ACh_F3↓/ACh_O1↓/ACh_T5↓/ACh_F7↓/NE_P3↑/NE_W↑/NE_C3↑/NE_F3↑/NE_O1↑/NE_T5↑/NE_F7↑ （F=13.43， whole brain）， ② 5-HT_O2↑/DA_O2↓/5-HT_P4↑/DA_P4↓/5-HT_W↑/DA_W↓/5-HT_C4↑/DA_C4↓ （F=5.94）， and ③ EXC_F4↓/DA_F4↓/NE_F4↑/INH_F4↑/5-HT_F4↑/ACh_F4↓ （F=5.33）. ConclusionThe actual 170 expression patterns of 6 neurotransmitters in the whole brain of 1 028 depression patients indicate that depression is a heterogeneous disease with individualized characteristics. The 22 characteristic expression patterns in the whole brain and 12 brain regions verify the pathogenesis hypothesis of multi-neurotransmitters oscillation imbalance in brains of depression patients. In summary， this study provides new guidance for the etiology， diagnosis， and treatment of depression and establishes a methodological foundation for the effectiveness evaluation of individualized treatment of depression by traditional Chinese medicine based on the objective biological markers.

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.

Neutrophil extracellular traps (NETs), intricate reticular structures released by activated neutrophils, play a pivotal regulatory role in the pathogenesis of malignant tumors. Lung cancer is one of the most prevalent malignancies globally, with persistently high incidence and mortality rates. Recent studies have revealed that NETs dynamically modulate the tumor microenvironment through unique pathological mechanisms, exhibiting complex immunoregulatory characteristics during the progression of lung cancer, and this discovery has increasingly become a focal point in tumor immunology research. This paper provides a comprehensive review of the latest advancements in NETs research related to lung cancer, offering an in-depth analysis of their impact on lung cancer progression, their potential diagnostic value, and the current state of research on targeting NETs for lung cancer prevention and treatment. The aim is to propose novel strategies to enhance therapeutic outcomes and improve the prognosis for lung cancer patients.
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Extracellular Traps/immunology* ; Humans ; Lung Neoplasms/metabolism* ; Neutrophils/metabolism* ; Animals ; Tumor Microenvironment

Protrusive facial deformities, characterized by the forward displacement of the teeth and/or jaws beyond the normal range, affect a considerable portion of the population. The manifestations and morphological mechanisms of protrusive facial deformities are complex and diverse, requiring orthodontists to possess a high level of theoretical knowledge and practical experience in the relevant orthodontic field. To further optimize the correction of protrusive facial deformities, this consensus proposes that the morphological mechanisms and diagnosis of protrusive facial deformities should be analyzed and judged from multiple dimensions and factors to accurately formulate treatment plans. It emphasizes the use of orthodontic strategies, including jaw growth modification, tooth extraction or non-extraction for anterior teeth retraction, and maxillofacial vertical control. These strategies aim to reduce anterior teeth and lip protrusion, increase chin prominence, harmonize nasolabial and chin-lip relationships, and improve the facial profile of patients with protrusive facial deformities. For severe skeletal protrusive facial deformities, orthodontic-orthognathic combined treatment may be suggested. This consensus summarizes the theoretical knowledge and clinical experience of numerous renowned oral experts nationwide, offering reference strategies for the correction of protrusive facial deformities.
Humans ; Orthodontics, Corrective/methods* ; Consensus ; Malocclusion/therapy* ; Patient Care Planning ; Cephalometry

Lumbar disc (LD) herniation and aging are prevalent conditions that can result in substantial morbidity. This study aimed to clarify the mechanisms connecting the LD aging and herniation, particularly focusing on cellular senescence and molecular alterations in the nucleus pulposus (NP). We performed a detailed analysis of NP samples from a diverse cohort, including individuals of varying ages and those with diagnosed LD herniation. Our methodology combined histological assessments with single-nucleus RNA sequencing to identify phenotypic and molecular changes related to NP aging and herniation. We discovered that cellular senescence and a decrease in nucleus pulposus progenitor cells (NPPCs) are central to both processes. Additionally, we found an age-related increase in NFAT1 expression that promotes NPPC senescence and contributes to both aging and herniation of LD. This research offers fresh insights into LD aging and its associated pathologies, potentially guiding the development of new therapeutic strategies to target the root causes of LD herniation and aging.
Intervertebral Disc Displacement/metabolism* ; Humans ; Aging/pathology* ; Nucleus Pulposus/pathology* ; Male ; Female ; Transcriptome ; Middle Aged ; Lumbar Vertebrae/pathology* ; Adult ; Cellular Senescence ; Stem Cells/pathology* ; Aged ; Intervertebral Disc Degeneration/metabolism*