ObjectiveTo investigate the role of 4-week high-intensity interval training (HIIT) in modulating the metabolic homeostasis of the pyruvate-lactate axis in the hippocampus of rats with chronic unpredictable mild stress (CUMS) to improve their depressive-like behavior. MethodsForty-eight SPF-grade 8-week-old male SD rats were randomly divided into 4 groups: the normal quiet group (C), the CUMS quiet group (M), the normal exercise group (HC), and the CUMS exercise group (HM). The M and HM groups received 8 weeks of CUMS modeling, while the HC and HM groups were exposed to 4 weeks of HIIT starting from the 5th week (3 min (85%-90%) S_max+1 min (50%-55%) S_max, 3-5 cycles, S_max is the maximum movement speed). A lactate analyzer was used to detect the blood lactate concentration in the quiet state of rats in the HC and HM groups at week 4 and in the 0, 2, 4, 8, 12, and 24 h after exercise, as well as in the quiet state of rats in each group at week 8. Behavioral indexes such as sucrose preference rate, number of times of uprightness and number of traversing frames in the absenteeism experiment, and other behavioral indexes were used to assess the depressive-like behavior of the rats at week 4 and week 8. The rats were anesthetized on the next day after the behavioral test in week 8, and hippocampal tissues were taken for assay. LC-MS non-targeted metabolomics, target quantification, ELISA and Western blot were used to detect the changes in metabolite content, lactate and pyruvate concentration, the content of key metabolic enzymes in the pyruvate-lactate axis, and the protein expression levels of monocarboxylate transporters (MCTs). Results4-week HIIT intervention significantly increased the sucrose preference rate, the number of uprights and the number of traversed frames in the absent field experiment in CUMS rats; non-targeted metabolomics assay found that 21 metabolites were significantly changed in group M compared to group C, and 14 and 11 differential metabolites were significantly dialed back in the HC and HM groups, respectively, after the 4-week HIIT intervention; the quantitative results of the targeting showed that, compared to group C, lactate concentration in the hippocampal tissues of M group, compared with group C, lactate concentration in hippocampal tissue was significantly reduced and pyruvate concentration was significantly increased, and 4-week HIIT intervention significantly increased the concentration of lactate and pyruvate in hippocampal tissue of HM group; the trend of changes in blood lactate concentration was consistent with the change in lactate concentration in hippocampal tissue; compared with group C, the LDHB content of group M was significantly increased, the content of PKM2 and PDH, as well as the protein expression level of MCT2 and MCT4 were significantly reduced. The 4-week HIIT intervention upregulated the PKM2 and PDH content as well as the protein expression levels of MCT2 and MCT4 in the HM group. ConclusionThe 4-week HIIT intervention upregulated blood lactate concentration and PKM2 and PDH metabolizing enzymes in hippocampal tissues of CUMS rats, and upregulated the expression of MCT2 and MCT4 transport carrier proteins to promote central lactate uptake and utilization, which regulated metabolic homeostasis of the pyruvate-lactate axis and improved depressive-like behaviors.

ObjectiveThis study aimed to investigate the effects of 4-week high-intensity interval training (HIIT) on synaptic plasticity in the prefrontal cortex (PFC) of rats exposed to chronic unpredictable mild stress (CUMS), and to explore its potential mechanisms. MethodsA total of 48 male Sprague-Dawley rats were randomly divided into 4 groups: control (C), model (M), control plus HIIT (HC), and model plus HIIT (HM). Rats in groups M and HM underwent 8 weeks of CUMS to establish depression-like behaviors, while groups HC and HM received HIIT intervention beginning from the 5th week for 4 consecutive weeks. The HIIT protocol consisted of repeated intervals of 3 min at high speed (85%-90% maximal training speed, S_max) alternated with one minute at low speed (50%-55% S_max), with 3 to 5 sets per session, conducted 5 d per week. Behavioral assessments and tail-vein blood lactate levels were measured at the end of the 4th and 8th weeks. After the intervention, rat PFC tissues were collected for Golgi staining to analyze synaptic morphology. Enzyme-linked immunosorbent assays (ELISA) were employed to detect brain-derived neurotrophic factor (BDNF), monocarboxylate transporter 1 (MCT1), lactate, and glutamate levels in the PFC, as well as serotonin (5-HT) levels in serum. Additionally, Western blot analysis was conducted to quantify the expression of synaptic plasticity-related proteins, including c-Fos, activity-regulated cytoskeleton-associated protein (Arc), and N-methyl-D-aspartate receptor 1 (NMDAR1). ResultsCompared to the control group (C), the CUMS-exposed rats (group M) exhibited significant reductions in sucrose preference rates, number of grid crossings, frequency of upright postures, and entries into and duration spent in open arms of the elevated plus maze, indicating marked depressive-like behaviors. Additionally, the group M showed significantly reduced dendritic spine density in the PFC, along with elevated levels of c-Fos, Arc, NMDAR1 protein expression, and increased concentrations of lactate and glutamate. Conversely, BDNF and MCT1 contents in the PFC and 5-HT levels in serum were significantly decreased. Following HIIT intervention, rats in the group HM displayed considerable improvement in behavioral indicators compared with the group M, accompanied by significant elevations in PFC MCT1 and lactate concentrations. Furthermore, HIIT notably normalized the expression levels of c-Fos, Arc, NMDAR1, as well as glutamate and BDNF contents in the PFC. Synaptic spine density also exhibited significant recovery. ConclusionFour weeks of HIIT intervention may alleviate depressive-like behaviors in CUMS rats by increasing lactate levels and reducing glutamate concentration in the PFC, thereby downregulating the overexpression of NMDAR, attenuating excitotoxicity, and enhancing synaptic plasticity.

Non-steroidal anti-inflammatory drugs(NSAIDs),commonly utilized analgesics,are extensively employed for managing pain associated with musculoskeletal disorders or injuries.Recent clinical studies have demonstrated a heightened risk of bone stress injuries(BSI)in soldiers and athletes,particularly during high-intensity training,due to NSAID usage.Furthermore,the impact of NSAIDs on fracture healing is well-documented;however,the precise mechanism by which their use during training contributes to an increased incidence of stress bone injuries remains unclear.This article aims to summarize potential mechanisms through an extensive review of domestic and international literature in order to standardize the utilization and clinical management of NSAIDs,optimize pain management strategies,and prevent stress bone injuries or fractures in specific populations such as soldiers and elite athletes.

Objective To investigate the role of the neutrophil-to-lymphocyte ratio(NLR)in predicting the in-hospital mortality risk of patients with acute aortic dissection(AAD)in multicenter hospitals.Methods A multicenter retrospective cohort study was conducted.Clinical data were collected from 2642 AAD patients who were hospitalized in five teaching hospitals:Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology,Henan Provincial People's Hospital,Fuwai Central China Cardiovascular Hospital,the Third Affiliated Hospital of Xinxiang Medical University,and the Second Affiliated Hospital of Chongqing Medical University between August 2010 and December 2021.According to the quartiles of serum NLRlevels,the patients were divided into four groups:first quartile(Q1,n=660),second quartile(Q2,n=661),third quartile(Q3,n=661),and fourth quartile(Q4,n=660).The clinical characteristics and biochemical indicators of each group were compared.Partial correlation analysis was used to assess the relationship between NLR and cardiovascular parameters.Restricted cubic splines,Kaplan-Meier survival analysis,and Cox regression models were employed to evaluate the association between NLR levels and in-hospital mortality risk in AAD patients.Results The median age of all patients was 54[interquartile range(IQR):46-63]years,including 2096 males and 546 females.Compared with Q1-Q3 groups,patients inQ4group had a lower incidence of smoking history and diabetes history,and were more likely to have DeBakey type Ⅰ AAD(P＜0.05).Additionally,the levels of aspartate aminotransferase,high-density lipoprotein cholesterol,creatinine,and D-dimer in Q4 group were higher,while the levels of triglycerides and C-reactive protein(CRP)were lower(P＜0.01).The results of partial correlation analysis showed that the plasma NLR level was positively correlated with D-dimer(r=0.43,P＜0.01)and creatinine(r=0.16,P＜0.01).The restricted cubic spline function in the Cox model revealed a significant non-linear relationship between the plasma NLR level and clinical outcomes in AAD patients(P＜0.01).Kaplan-Meier survival analysis indicated that patients in Q4 group had the highest in-hospital mortality rate compared with Q1-Q3 groups(P＜0.0001).Furthermore,multivariate Cox regression analysis demonstrated that compared with Q1 group,the hazard ratio(HR)of NLR in Q4 group was 1.77(95％CI 1.33-2.37,P＜0.001),which was an independent risk factor for the primary endpoint events.Conclusion A higher plasma NLR level is significantly associated with the occurrence of cardiovascular events in AAD patients,and this association remains significant even after adjusting for potential confounding factors such as the multicenter visiting hospitals.

Purpose: This study evaluated volumetric analysis using automatic whole-brain segmentation as a potential tool to enhance diagnostic accuracy alongside traditional magnetic resonance imaging (MRI) markers in the diagnosis of idiopathic normal pressure hydrocephalus (INPH). Materials and Methods: Twenty-six patients diagnosed with INPH exhibited progressive symptoms, including gait dysfunction and cognitive impairment, confirmed by MRI evidence of enlarged ventricles and normal cerebrospinal fluid pressure. Automatic segmentation was performed on sagittal T1-weighted volumetric images using LesionQuant. Age- and sex-matched groups with Alzheimer’s disease (AD) and normal control (NC) groups were included. Multinomial logistic regression was applied to predict diagnoses (NC, INPH, or AD) based on volumetric parameters. Results: Compared to the AD and NC groups, enlarged inferior lateral ventricles were observed in the INPH group. The inferior lateral ventricle volume showed a positive linear correlation with the Evans’ index (R2 = 0.639) and a negative linear correlation with the callosal angle (R2 = 0.482). High classification accuracy was achieved, with 87.5% of NC cases, 88.5% of INPH cases, and 76% of AD cases correctly identified. Conclusion Automated volumetric markers appear valuable for diagnosing INPH and distinguishing it from other neurodegenerative diseases.

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.

Purpose: This study evaluated volumetric analysis using automatic whole-brain segmentation as a potential tool to enhance diagnostic accuracy alongside traditional magnetic resonance imaging (MRI) markers in the diagnosis of idiopathic normal pressure hydrocephalus (INPH). Materials and Methods: Twenty-six patients diagnosed with INPH exhibited progressive symptoms, including gait dysfunction and cognitive impairment, confirmed by MRI evidence of enlarged ventricles and normal cerebrospinal fluid pressure. Automatic segmentation was performed on sagittal T1-weighted volumetric images using LesionQuant. Age- and sex-matched groups with Alzheimer’s disease (AD) and normal control (NC) groups were included. Multinomial logistic regression was applied to predict diagnoses (NC, INPH, or AD) based on volumetric parameters. Results: Compared to the AD and NC groups, enlarged inferior lateral ventricles were observed in the INPH group. The inferior lateral ventricle volume showed a positive linear correlation with the Evans’ index (R2 = 0.639) and a negative linear correlation with the callosal angle (R2 = 0.482). High classification accuracy was achieved, with 87.5% of NC cases, 88.5% of INPH cases, and 76% of AD cases correctly identified. Conclusion Automated volumetric markers appear valuable for diagnosing INPH and distinguishing it from other neurodegenerative diseases.

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.

Purpose: This study evaluated volumetric analysis using automatic whole-brain segmentation as a potential tool to enhance diagnostic accuracy alongside traditional magnetic resonance imaging (MRI) markers in the diagnosis of idiopathic normal pressure hydrocephalus (INPH). Materials and Methods: Twenty-six patients diagnosed with INPH exhibited progressive symptoms, including gait dysfunction and cognitive impairment, confirmed by MRI evidence of enlarged ventricles and normal cerebrospinal fluid pressure. Automatic segmentation was performed on sagittal T1-weighted volumetric images using LesionQuant. Age- and sex-matched groups with Alzheimer’s disease (AD) and normal control (NC) groups were included. Multinomial logistic regression was applied to predict diagnoses (NC, INPH, or AD) based on volumetric parameters. Results: Compared to the AD and NC groups, enlarged inferior lateral ventricles were observed in the INPH group. The inferior lateral ventricle volume showed a positive linear correlation with the Evans’ index (R2 = 0.639) and a negative linear correlation with the callosal angle (R2 = 0.482). High classification accuracy was achieved, with 87.5% of NC cases, 88.5% of INPH cases, and 76% of AD cases correctly identified. Conclusion Automated volumetric markers appear valuable for diagnosing INPH and distinguishing it from other neurodegenerative diseases.