Association of time spent outdoors with the risk of Parkinson's disease: a prospective cohort study of 329,359 participants.

BACKGROUND: Studies on the association between time spent outdoors and the development of Parkinson's disease (PD) are lacking, and whether this relationship differs in different subgroups (age, sex) remains unclear. OBJECTIVE: We here examined the association between time spent outdoors and the incidence of PD in different seasons. METHODS: This study included 329,359 participants from the UK Biobank. Data regarding hours spent outdoors during a typical day were obtained through questionnaires. Cox proportional hazard regression models were used to estimate hazard ratios (HRs) for the association between exposure to outdoors duration and PD incidence. Restricted cubic spline was used to explore the potential nonlinear relationship between time spent outdoors and PD risk. To explore the potential mechanisms of time spent outdoors effecting the risk of PD incidence, their association with serum vitamin D was further analysed separately. RESULTS: During a median follow-up of 13.57 years, 2,238 participants developed PD. In summer, time spent outdoors > 5.0 h/day was associated with a reduced PD risk compared with ≤ 2.0 h/day (HR = 0.84, 95% CI, 0.74-0.95). In winter too, time spent outdoors > 2.0 h/day was also associated with a reduced PD risk compared with ≤ 1.0 h/day (HR = 0.85, 95% CI, 0.76-0.94). For annual average time spent outdoors, participants who went outdoors for more than 3.5 h/day had a reduced PD risk than those who went outdoors for ≤ 1.5 h/day (HR = 0.85, 95% CI, 0.75-0.96). Additionally, sex and age differences were observed in the association between time spent outdoors and the PD risk. Moreover, Time spent outdoors was observed to be positively associated with serum vitamin D levels. Compared with serum vitamin D-deficient participants, the risk of PD was reduced by 15% in the sufficient participants. CONCLUSION: In the total population, higher time spent outdoors was linked to a reduced PD risk. However, this association may vary among different age or sex groups.

Early-life tobacco smoke exposure and stroke risk: a prospective study of 341,783 and 352,737 UK Biobank participants.

INTRODUCTION: Stroke is a life-threatening condition that causes a major medical burden globally. The currently used methods for the prevention or prediction of stroke have certain limitations. Exposure to tobacco in early life, including smoking during adolescence and maternal smoking during pregnancy, can affect adolescent development and lead to several negative outcomes. However, the association between early-life tobacco exposure and stroke is not known. METHODS: In this prospective cohort study, for the analyses involving exposure to maternal smoking during pregnancy and age of smoking initiation, we included 304,984 and 342,893 participants, respectively., respectively from the UK Biobank. Cox proportional hazard regression model and subgroup analyses were performed to investigate the association between early-life tobacco exposure and stroke. Mediation analyses were performed to identify the mediating role of biological aging in the association between early tobacco exposure and stroke. RESULTS: Compared with participants whose mothers did not smoke during pregnancy, participants whose mothers smoked during pregnancy showed an 11% increased risk of stroke (HR: 1.11, 95% CI: 1.05-1.18, P < 0.001). Compared with participants who never smoked, participants who smoked during adulthood, adolescence and childhood showed a 22%, 24%, and 38% increased risk of stroke during their adulthood, respectively. Mediation analysis indicated that early-life tobacco exposure can cause stroke by increasing biological aging. CONCLUSION: This study reveals that exposure to tobacco during early life is associated with an increased risk of experiencing a stroke, and increased biological aging can be the underlying mechanism.

Association of pro-inflammatory diet with increased risk of all-cause dementia and Alzheimer's dementia: a prospective study of 166,377 UK Biobank participants.

BACKGROUND: Increasing evidence suggests an association between pro-inflammatory diets and cognitive function. However, only a few studies based on small sample sizes have explored the association between pro-inflammatory diets and dementia using the dietary inflammatory index (DII). Additionally, the relationship between DII and different subtypes of dementia, such as Alzheimer's dementia and vascular dementia, remains largely unexplored. Given the changes in brain structure already observed in patients with dementia, we also investigated the association between DII and magnetic resonance imaging (MRI) measures of brain structure to provide some hints to elucidate the potential mechanisms between pro-inflammatory diet and cognitive decline. METHODS: A total of 166,377 UK Biobank participants without dementia at baseline were analyzed. DII calculations were based on the information collected by the 24-h recall questionnaire. Brain structural anatomy and tissue-specific volumes were measured using brain MRI. Cox proportional hazards models, competing risk models, and restricted cubic spline were applied to assess the longitudinal associations. The generalized linear model was used to assess the association between DII and MRI measurements. RESULTS: During a median follow-up time of 9.46 years, a total of 1372 participants developed dementia. The incidence of all-cause dementia increased by 4.6% for each additional unit of DII [hazard ratio (HR): 1.046]. Besides, DII displayed a "J-shaped" non-linear association with Alzheimer's dementia (Pnonlinear = 0.003). When DII was above 1.30, an increase in DII was significantly associated with an increased risk of Alzheimer's dementia (HR: 1.391, 95%CI: 1.085-1.784, P = 0.009). For brain MRI, the total volume of white matter hyperintensities increased with an increase in DII, whereas the volume of gray matter in the hippocampus decreased. CONCLUSIONS: In this cohort study, higher DII was associated with a higher risk of all-cause dementia and Alzheimer's dementia. However, our findings suggested that the association with DII and vascular and frontotemporal dementia was not significant.

Comparative efficacy and safety of monoamine oxidase type B inhibitors plus channel blockers and monoamine oxidase type B inhibitors as adjuvant therapy to levodopa in the treatment of Parkinson's disease: a network meta-analysis of randomized controlled trials.

BACKGROUND AND PURPOSE: The monoamine oxidase type B inhibitors plus channel blockers (MAO-BIs plus) are a new class of antiparkinsonian drug with additional mechanisms of action for their property as ion channel blockers. The present study aimed to compare the efficacy and safety of MAO-BIs plus and conventional MAO-BIs, as well as their corresponding doses, as adjuvant therapy to levodopa in the treatment of Parkinson's disease (PD). METHOD: Randomized controlled trials enrolling PD patients treated with selegiline, rasagiline, safinamide or zonisamide as adjuvant therapy to levodopa were identified. Bayesian network meta-analysis was conducted. RESULTS: Thirty-one randomized controlled trials comprising 7142 PD patients were included. Compared with levodopa monotherapy, the combination therapy of MAO-BIs and levodopa was significantly more effective, with a mean difference of 2.74 (1.26-4.18) on the Unified Parkinson's Disease Rating Scale (UPDRS) III score change for selegiline, 2.67 (1.45-3.87) for safinamide, 2.2 (0.98-3.64) for zonisamide and 2.04 (1.24-2.87) for rasagiline. No significant difference was detected amongst MAO-BIs. The surface under the cumulative ranking results showed that safinamide 100 mg and rasagiline 1 mg ranked first in improving UPDRS III and UPDRS II, respectively. Zonisamide 100 mg ranked first in reducing OFF time. For safety outcomes, rasagiline was associated with a higher incidence of adverse events than placebo and safinamide. MAO-BIs plus had a higher probability of being safer agents compared to conventional MAO-BIs. CONCLUSIONS: Monoamine oxidase type B inhibitors plus, conventional MAO-BIs and the corresponding doses are similar in efficacy in PD treatment. MAO-BIs plus might be safer than conventional MAO-BIs. Head-to-head comparisons are needed for further investigation.

Efficacy of short pulse and conventional deep brain stimulation in Parkinson's disease: a systematic review and meta-analysis.

BACKGROUND: Deep brain stimulation (DBS) is a common treatment for Parkinson's disease. However, the clinical efficacy of short pulse width DBS (spDBS) compared with conventional DBS (cDBS) is still unknown. OBJECTIVE: This meta-analysis investigated the effectiveness of spDBS versus cDBS in patients with PD. METHODS: Four databases (PubMed, Cochrane, Web of Science, and Embase) were independently searched until October 2021 by two reviewers. We utilized the following scales and items: therapeutic windows (TW), efficacy threshold, side effect threshold, Movement Disorder Society-Sponsored Revision Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III off-medication score, Speech Intelligence Test (SIT), and Freezing of Gait Questionnaire (FOG-Q). RESULTS: The analysis included seven studies with a total of 87 patients. The results indicated that spDBS significantly widened the therapeutic windows (0.99, 95% CI = 0.61 to 1.38) while increasing the threshold amplitudes of side effects (2.25, 95% CI = 1.69 to 2.81) and threshold amplitudes of effects (1.60, 95% CI = 0.84 to 2.36). There was no statistically significant difference in UPDRS part III, SIT, and FOG-Q scores between spDBS and cDBS groups, suggesting that treatment with both cDBS and spDBS may result in similar effects of improved dysarthria and gait disorders. CONCLUSIONS: Compared with cDBS, spDBS is effective in expanding TW. Both types of deep brain stimulation resulted in improved gait disorders and speech intelligibility.

Comparison of efficacy of deep brain stimulation and focused ultrasound in parkinsonian tremor: a systematic review and network meta-analysis.

To compare the efficacy of deep brain stimulation (DBS) and MRI-guided focused ultrasound (MRIgFUS) in parkinsonian tremor. We performed a network meta-analysis based on a Bayesian framework. We searched the literature for articles published between January 1990 and October 2020 using three databases: PubMed, Embase and Cochrane Library (The Cochrane Database of Systematic Reviews). A total of 24 studies were included in our analysis, comprising data from 784 participants. Our findings revealed similar efficacy of DBS and MRIgFUS in parkinsonian tremor suppression. Compared with internal globus pallidus (GPi)-MRIgFUS, GPi-DBS -1.84 (-6.44, 2.86), pedunculopontine nucleus (PPN)_DBS -3.28 (-9.28, 2.78), PPN and caudal zona incerta (cZI)-DBS 0.40 (-6.16, 6.87), subthalamic nucleus (STN)_DBS 0.89 (-3.48, 5.30), STN and cZI-DBS 1.99 (-4.74, 8.65), ventral intermediate nucleus(VIM)_DBS 1.75 (-2.87, 6.48), VIM_FUS 0.72 (-5.27, 6.43), cZI-DBS 0.27 (-4.75, 5.36) were no significantly difference. Compared with VIM-MRIgFUS, GPi-DBS -2.55(-6.94, 2.21), GPi-FUS -0.72 (-6.43, 5.27), PPN_DBS -4.01(-9.97, 2.11), PPN and cZI-DBS -0.32 (-6.73, 6.36), STN_DBS 0.16 (-3.98, 4.6), STN and cZI-DBS 1.31(-5.18,7.87), VIM-DBS 1.00(-3.41, 5.84)and cZI-DBS -0.43 (-5.07, 4.68) were no significantly difference. With respect to the results for the treatment of motor symptoms, GPi-DBS, GPi-MRIgFUS, STN-DBS and cZI-DBS were significantly more efficacious than baseline (GPi-DBS 15.24 (5.79, 24.82), GPi-MRIgFUS 13.46 (2.46, 25.10), STN-DBS 19.62 (12.19, 27.16), cZI-DBS 14.18 (1.73, 26.89). The results from the surface under the cumulative ranking results showed that STN-DBS ranked first, followed by combined PPN and cZI-DBS, and PPN-DBS ranked last. MRIgFUS, an efficacious intervention for improving parkinsonian tremor, has not demonstrated to be inferior to DBS in parkinsonian tremor suppression. Hence, clinicians should distinguish individual patients' symptoms to ensure that the appropriate intervention and therapeutic approach are applied.

Pedunculopontine Nucleus Deep Brain Stimulation Improves Gait Disorder in Parkinson's Disease: A Systematic Review and Meta-analysis.

Deep brain stimulation (DBS) of the pedunculopontine nucleus (PPN) has been proposed as a treatment strategy for gait disorder in patients with Parkinson's disease (PD). We thus performed a systematic review and meta-analysis of randomized and nonrandomized controlled trials to assess the effect of this treatment on gait disorder in patients with PD. We systematically searched PubMed, Cochrane, Web of Knowledge, Wan Fang and WIP for randomized and nonrandomized controlled trials (published before July 29, 2014; no language restrictions) comparing PPN-DBS with other treatments. We assessed pooled data using a random effects model and a fixed effects model. Of 130 identified studies, 14 were eligible and were included in our analysis (N = 82 participants). Compared to those presurgery, the Unified Parkinson Disease Rating Scale (UPDRS) 27-30 scores for patients were lowered by PPN-DBS [3.94 (95% confidence interval, CI = 1.23 to 6.65)]. The UPDRS 13 and 14 scores did not improve with levodopa treatment [0.43 (- 0.35 to 1.20); 0.35 (- 0.50 to 1.19)], whereas the UPDRS 27-30 scores could be improved by the therapy [1.42 (95% CI 0.34 to 2.51)]. The Gait and Falls Questionnaire and UPDRS 13 and 14 scores showed significant improvements after PPN-DBS under the medication-off (MED-OFF) status [15.44 (95% CI = 8.44 to 22.45); 1.57 (95% CI = 0.84 to 2.30); 1.34 (95% CI = 0.84 to 1.84)]. PPN-DBS is a potential therapeutic target that could improve gait and fall disorders in patients with PD. Our findings will help improve the clinical application of DBS in PD patients with gait disorder.

Association between 2,4-dichlorophenoxyacetic acid and cognitive impairment in older adults: a cross-sectional study from NHANES 2001-2002 and 2011-2014.

BACKGROUND: 2,4-Dichlorophenoxyacetic acid (2,4-D) is reported to be the most widely used herbicide in home and garden environments, rendering it commonly encountered in daily life. Despite being ubiquitous, there is a scarcity of studies that have comprehensively assessed the relationship between 2,4-D exposure and cognition using multiple models. OBJECTIVE: To explore the association between 2,4-D exposure and cognition among older American people. METHODS: This was a cross-sectional study that included 3 cycles of data from the National Health and Nutrition Examination Survey. Generalized linear models (GLMs), restricted cubic spline (RCS) regression, and generalized additive models (GAMs) were used to assess the relationship between exposure to 2,4-D and cognitive performance by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) word learning sub-test, Digit Symbol Substitution Test (DSST), and Animal Fluency Test (AFT). RESULTS: A total of 1364 older U.S. adults (60+ years) were included in the study. The GLMs revealed a negative association between median high levels (0.315-0.566 µg/L) of 2,4-D and cognitive impairment on the DSST and AFT, with multivariate-adjusted ORs of 0.403 (95% CI: 0.208-0.781, P = 0.009) and 0.396 (95% CI: 0.159-0.986, P = 0.047); the RCS regression and GAMs revealed a "U" shaped curve, the left part of which is consistent with the result of the GLMs. IMPACT STATEMENT: There is a U-shaped relationship between human urinary 2,4-D concentrations and cognitive impairment in older U.S. adults, especially in males, so controlling 2,4-D exposure within an appropriate range is particularly important for cognitive function.

Development of a predictive model for 1-year postoperative recovery in patients with lumbar disk herniation based on deep learning and machine learning.

Background: The aim of this study is to develop a predictive model utilizing deep learning and machine learning techniques that will inform clinical decision-making by predicting the 1-year postoperative recovery of patients with lumbar disk herniation. Methods: The clinical data of 470 inpatients who underwent tubular microdiscectomy (TMD) between January 2018 and January 2021 were retrospectively analyzed as variables. The dataset was randomly divided into a training set (n = 329) and a test set (n = 141) using a 10-fold cross-validation technique. Various deep learning and machine learning algorithms including Random Forests, Extreme Gradient Boosting, Support Vector Machines, Extra Trees, K-Nearest Neighbors, Logistic Regression, Light Gradient Boosting Machine, and MLP (Artificial Neural Networks) were employed to develop predictive models for the recovery of patients with lumbar disk herniation 1 year after surgery. The cure rate score of lumbar JOA score 1 year after TMD was used as an outcome indicator. The primary evaluation metric was the area under the receiver operating characteristic curve (AUC), with additional measures including decision curve analysis (DCA), accuracy, sensitivity, specificity, and others. Results: The heat map of the correlation matrix revealed low inter-feature correlation. The predictive model employing both machine learning and deep learning algorithms was constructed using 15 variables after feature engineering. Among the eight algorithms utilized, the MLP algorithm demonstrated the best performance. Conclusion: Our study findings demonstrate that the MLP algorithm provides superior predictive performance for the recovery of patients with lumbar disk herniation 1 year after surgery.

Hypoxic-preconditioned mesenchymal stem cell-derived small extracellular vesicles promote the recovery of spinal cord injury by affecting the phenotype of astrocytes through the miR-21/JAK2/STAT3 pathway.

BACKGROUND: Secondary injury after spinal cord injury (SCI) is a major obstacle to their neurological recovery. Among them, changes in astrocyte phenotype regulate secondary injury dominated by neuroinflammation. Hypoxia-preconditioned mesenchymal stem cells (MSCs)-derived extracellular vesicle (H-EV) plays a multifaceted role in secondary injury by interacting with cellular components and signaling pathways. They possess anti-inflammatory properties, regulate oxidative stress, and modulate apoptotic pathways, promoting cell survival and reducing neuronal loss. Given the unique aspects of secondary injury, H-EV shows promise as a therapeutic approach to mitigate its devastating consequences. Our study aimed to determine whether H-EV could promote SCI repair by altering the phenotype of astrocytes. METHODS: Rat bone marrow MSCs (BMSCs) and EVs secreted by them were extracted and characterized. After the SCI model was successfully constructed, EV and H-EV were administered into the tail vein of the rats, respectively, and then their motor function was evaluated by the Basso-Beattie-Bresnahan (BBB) score, Catwalk footprint analysis, and electrophysiological monitoring. The lesion size of the spinal cord was evaluated by hematoxylin-eosin (HE) staining. The key point was to use glial fibrillary acidic protein (GFAP) as a marker of reactive astrocytes to co-localize with A1-type marker complement C3 and A2-type marker S100A10, respectively, to observe phenotypic changes in astrocytes within tissues. The western blot (WB) of the spinal cord was also used to verify the results. We also compared the efficacy differences in apoptosis and inflammatory responses using terminal deoxynucleotidyl transferase dUTP terminal labeling (TUNEL) assay, WB, and enzyme-linked immunosorbent assay (ELISA). Experiments in vitro were also performed to verify the results. Subsequently, we performed microRNA (miRNA) sequencing analysis of EV and H-EV and carried out a series of knockdown and overexpression experiments to further validate the mechanism by which miRNA in H-EV plays a role in promoting astrocyte phenotypic changes, as well as the regulated signaling pathways, using WB both in vivo and in vitro. RESULTS: Our findings suggest that H-EV is more effective than EV in the recovery of motor function, anti-apoptosis, and anti-inflammatory effects after SCI, both in vivo and in vitro. More importantly, H-EV promoted the conversion of A1 astrocytes into A2 astrocytes more than EV. Moreover, miR-21, which was found to be highly expressed in H-EV by miRNA sequencing results, was also demonstrated to influence changes in astrocyte phenotype through a series of knockdown and overexpression experiments. At the same time, we also found that H-EV might affect astrocyte phenotypic alterations by delivering miR-21 targeting the JAK2/STAT3 signaling pathway. CONCLUSION: H-EV exerts neuroprotective effects by delivering miR-21 to promote astrocyte transformation from the A1 phenotype to the A2 phenotype, providing new targets and ideas for the treatment of SCI.

Association of Exposure to Ambient Air Pollutants With Cognitive Performance and Dementia Risk and the Mediating Role of Pulmonary Function: Evidence From the UK Biobank.

BACKGROUND: The pathways by which air pollution affects cognition remain to be explored. This study aimed to explore how single air pollutants [including nitrogen oxide (NOX), nitrogen dioxide (NO2), particulate matter with a diameter of 2.5 micrometers (PM2.5), PM10, and PM2.5-10], and air pollution mixture could affect cognitive function and the incidence of dementia, and determine whether pulmonary function (PF) could play a mediating role in the relationship. METHODS: Multiple statistical methods were employed to evaluate association of 5 air pollutants (NOX, NO2, PM2.5, PM10, and PM2.5-10) with cognitive function. Bootstrap method was used to estimate mediating role of PF in the association of air pollutants with cognition or the incidence of dementia. RESULTS: A mixture of air pollutants was associated with performance on 5 cognitive tests, and global cognition (p < .05). Significantly negative association was also identified between mixture of air pollutants and PF (ß= -0.020, 95% confidence interval (CI) = -0.029 to -0.011). In addition, as PF scores increase, performance on all cognitive tests significantly improve, although the risk of dementia correspondingly decreases. It was noted that PF was shown to mediate the effects of air pollution mixtures on all cognitive tests as well as global cognition. For global cognition, PF mediated 6.08% of the association. PF was also found to have a mediating role in the association between NOX, NO2, PM2.5, and the risk of dementia. CONCLUSIONS: Mixed air pollution may impact cognitive function, with PF potentially mediating this relationship.

Accelerated biological aging as potential mediator mediates the relationship between pro-inflammatory diets and the risk of depression and anxiety: A prospective analysis from the UK biobank.

BACKGROUND: The relationship between inflammatory dietary patterns and the risk of depression/anxiety has not been clearly established due to differences in study populations, geographic regions, sex, and methods of calculating the inflammatory index. METHODS: We drew upon a prospective cohort in the UK Biobank and calculated the energy-adjusted dietary inflammatory index (E-DII). The follow-up time was defined from the date of completing the last dietary survey questionnaire to the date of diagnosis of depression, anxiety, phobic anxiety, other types of anxiety, death, loss to follow-up, or the respective censoring dates for England (September 30, 2021), Scotland (July 31, 2021), and Wales (February 28, 2018). The final follow-up times end on September 30, 2021, July 31, 2021, and February 28, 2018, for England, Scotland, and Wales, respectively. During the follow-up process, if a participant develops the condition, dies, or is lost to follow-up, the follow-up is terminated. We used Cox regression to evaluate the connection between E-DII and depression/anxiety. We employed restricted cubic spline curves for nonlinear relationships. We also conducted mediation analyses to explore whether biological age mediated the relationship between E-DII and depression. Additionally, we investigated whether genetic susceptibility modified the relationship between E-DII and depression through interaction modeling. RESULTS: In the final analysis, we included a total of 151,295, 159,695, 165,649, and 160,097 participants for the analysis of depression, all types of anxiety, specific phobia anxiety, and other types of anxiety, respectively. For every one-unit increase in E-DII, the risk of experiencing depression and anxiety increased by 5 % and 4 %, respectively. We identified a "J"-shaped nonlinear relationship (P for nonlinear = 0.003) for both depression and anxiety. A significant association with an elevated risk of depression was observed when E-DII exceeded 0.440, and an increased risk of anxiety was noted when E-DII was more than -0.196. Mediation analysis demonstrated that PhenoAge age acceleration (AA) (For depression, proportion of mediation = 9.6 %; For anxiety, proportion of mediation = 10.1 %) and Klemera-Doubal method Biological Age (KDM AA) (For depression, proportion of mediation = 2.9 %; For anxiety, proportion of mediation = 5.1 %) acted as mediators between E-DII and the development of depression and anxiety (P < 0.05). CONCLUSIONS: Diets with pro-inflammatory characteristics are associated with a heightened risk of depression and anxiety. Furthermore, the association of pro-inflammatory diets and depression is mediated by biological age.

Cortical thickness and white matter microstructure predict freezing of gait development in Parkinson's disease.

The clinical applications of the association of cortical thickness and white matter fiber with freezing of gait (FoG) are limited in patients with Parkinson's disease (PD). In this retrospective study, using white matter fiber from diffusion-weighted imaging and cortical thickness from structural-weighted imaging of magnetic resonance imaging, we investigated whether a machine learning-based model can help assess the risk of FoG at the individual level in patients with PD. Data from the Parkinson's Disease Progression Marker Initiative database were used as the discovery cohort, whereas those from the Fujian Medical University Union Hospital Parkinson's Disease database were used as the external validation cohort. Clinical variables, white matter fiber, and cortical thickness were selected by random forest regression. The selected features were used to train the support vector machine(SVM) learning models. The median area under the receiver operating characteristic curve (AUC) was calculated. Model performance was validated using the external validation cohort. In the discovery cohort, 25 patients with PD were defined as FoG converters (15 men, mean age 62.1 years), whereas 60 were defined as FoG nonconverters (38 men, mean age 58.5 years). In the external validation cohort, 18 patients with PD were defined as FoG converters (8 men, mean age 66.9 years), whereas 37 were defined as FoG nonconverters (21 men, mean age 65.1 years). In the discovery cohort, the model trained with clinical variables, cortical thickness, and white matter fiber exhibited better performance (AUC, 0.67-0.88). More importantly, SVM-radial kernel models trained using random over-sampling examples, incorporating white matter fiber, cortical thickness, and clinical variables exhibited better performance (AUC, 0.88). This model trained using the above mentioned features was successfully validated in an external validation cohort (AUC, 0.91). Furthermore, the following minimal feature sets that were used: fractional anisotropy value and mean diffusivity value for right thalamic radiation, age at baseline, and cortical thickness for left precentral gyrus and right dorsal posterior cingulate gyrus. Therefore, machine learning-based models using white matter fiber and cortical thickness can help predict the risk of FoG conversion at the individual level in patients with PD, with improved performance when combined with clinical variables.

Left corticospinal tract could be a biomarker to identify the dual prodromal LRRK2/GBA mutated Parkinson's disease.

INTRODUCTION: Prodromal Parkinson's disease (PD) carriers of dual leucine-rich repeat kinase 2 (LRRK2) and glucosylceramidase ß (GBA) variants are rare, and their biomarkers are less well developed. OBJECTIVE: This study aimed to investigate the biomarkers for diagnosing the prodromal phase of LRRK2-GBA-PD (LRRK2-GBA-prodromal). METHODS: We assessed the clinical and whole-brain white matter microstructural characteristics of 54 prodromal PD carriers of dual LRRK2 (100% M239T) and GBA (95% N409S) variants, along with 76 healthy controls (HCs) from the Parkinson's Progression Markers Initiative (PPMI) cohort. RESULTS: By analyzing the four values of 100 nodes on 20 fiber bundles, totaling 8000 data points, we identified the smallest p value in the fractional anisotropy (FA) value of the 38th segment of left corticospinal tract (L-CST) with differences between LRRK2-GBA-prodromal and HCs (p = 8.94 × 10-9). The FA value of the 38th node of the L-CST was significantly lower in LRRK2-GBA-prodromal (FA value, 0.65) compared with HCs (FA value, 0.71). The receiver-operating characteristic curve showed a cut-off value of 0.218 for the FA value of L-CST, providing sufficient sensitivity (79.2%) and specificity (72.2%) to distinguish double mutation prodromal PD from the healthy population. CONCLUSION: L-CST, especially the 38th node, may potentially serve as a biomarker for distinguishing individuals with double mutation prodromal PD from the healthy population.

Association of physical activity pattern and risk of Parkinson's disease.

Increasing evidence suggests an association between exercise duration and Parkinson's disease. However, no high-quality prospective evidence exists confirming whether differences exist between the two modes of exercise, weekend warrior and equal distribution of exercise duration, and Parkinson's risk. Hence, this study aimed to explore the association between different exercise patterns and Parkinson's risk using exercise data from the UK Biobank. The study analyzed data from 89,400 UK Biobank participants without Parkinson's disease. Exercise data were collected using the Axivity AX3 wrist-worn triaxial accelerometer. Participants were categorized into three groups: inactive, regularly active, and engaged in the weekend warrior (WW) pattern. The relationship between these exercise patterns and Parkinson's risk was assessed using a multifactorial Cox model. During a mean follow-up of 12.32 years, 329 individuals developed Parkinson's disease. In a multifactorial Cox model, using the World Health Organization-recommended threshold of 150 min of moderate-to-vigorous physical activity per week, both the active WW group [hazard ratio (HR) = 0.58; 95% confidence interval (CI) = 0.43-0.78; P < 0.001] and the active regular group (HR = 0.44; 95% CI = 0.34-0.57; P < 0.001) exhibited a lower risk of developing Parkinson's disease compared with the inactive group. Further, no statistically significant difference was observed between the active WW and the active regular groups (HR = 0.77; 95% CI = 0.56-1.05; P = 0.099). In conclusion, in this cohort study, both the WW exercise pattern and an equal distribution of exercise hours were equally effective in reducing Parkinson's risk.

Association between ethylene oxide levels and depressive symptoms: A cross-sectional study based on NHANES 2013-2018 database.

BACKGROUND AND AIM: Ethylene oxide (EO) is a commonly used compound with known health risks. However, the specific association between EO exposure and the development of depressive symptoms has not been well established. Therefore, this study aimed to examine the potential association between EO exposure, as indicated by hemoglobin adduct of ethylene oxide (HbEO) levels, and the occurrence of depressive symptoms. METHODS: We employed logistic regression, restricted cubic spline, and subgroup analysis to investigate the association between EO exposure and the occurrence of depressive symptoms. Additionally, we conducted a mediating effect analysis to explore the potential factors influencing the association between EO exposure and depressive symptoms. RESULTS: Elevated HbEO levels were associated with the development of depressive symptoms. After adjusting for potential confounders, the highest quartile of HbEO levels showed an odds ratio (OR) of 3.37 [95 % confidence interval (CI): 1.87-6.10, P = 0.002] compared with the lowest quartile. Additionally, a linear association was observed between HbEO levels and the risk of depressive symptoms. We also revealed that the levels of several inflammatory factors and triglycerides mediated the association between EO exposure and the occurrence of depressive symptoms. CONCLUSIONS: Higher levels of EO exposure were related to an increased risk of developing depressive symptoms. The analysis also suggested that the inflammatory response might play a mediating role in the pathway from EO exposure to depressive symptoms.

Association between exposure to phenols and parabens and cognitive function in older adults in the United States: A cross-sectional study.

BACKGROUND: People are commonly exposed to mixtures of parabens and phenols. Most studies investigating such exposure and cognitive performance tend to assess only single chemicals, and the tools used to assess cognitive function are not uniform. OBJECTIVE: This study aimed to examine the association between multiple parabens and phenols and cognitive function in older Americans. METHODS: The study included data of older Americans from two cycles of the NHANES survey. Participants were divided into normal cognitive performance and low cognitive performance groups based on the scores of four cognitive tests: the Immediate Recall test (IRT), the Delayed Recall test (DRT), the Animal Fluency test (AFT) and the Digit Symbol Substitution test (DSST). Generalized linear regression models (GLMs), restricted cubic spline (RCS), weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) were used to assess relationships between chemical exposure and cognitive performance. RESULTS: In this cross-sectional study, a total of 961 participants, 470 males and 491 females, were included. GLMs revealed positive association between high levels of bisphenol A (BPA) and low cognitive performance on DRT, especially in male (OR (95%CI): 2.25 (1.10-4.61)), and this association was consistent with WQS and BKMR. In female participants, the third quartile of BPA exposure showed a positive association with low cognition on IRT and global cognition. GLMs also showed that high levels of propylparaben were positively associated with cognitive performance on the IRT in male participants (OR (95%CI): 0.37 (0.18-0.76)). In BKMR, an overall positive correlation between the mixture and low cognition as measured with DRT was observed in male subjects when the mixture was at the 65th percentile or higher. CONCLUSION: Exposure to a mixture of parabens and phenols was positively associated with low cognitive performance on DRT in older male subjects, while BPA was the main driver of this outcome.

Development, validation, and visualization of a web-based nomogram to predict the effect of tubular microdiscectomy for lumbar disc herniation.

Objective: The purpose of this study was to retrospectively collect the relevant clinical data of lumbar disc herniation (LDH) patients treated with the tubular microdiscectomy (TMD) technique, and to develop and validate a prediction model for predicting the treatment improvement rate of TMD in LDH patients at 1 year after surgery. Methods: Relevant clinical data of LDH patients treated with the TMD technology were retrospectively collected. The follow-up period was 1 year after surgery. A total of 43 possible predictors were included, and the treatment improvement rate of the Japanese Orthopedic Association (JOA) score of the lumbar spine at 1 year after TMD was used as an outcome measure. The least absolute shrinkage and selection operator (LASSO) method was used to screen out the most important predictors affecting the outcome indicators. In addition, logistic regression was used to construct the model, and a nomogram of the prediction model was drawn. Results: A total of 273 patients with LDH were included in this study. Age, occupational factors, osteoporosis, Pfirrmann classification of intervertebral disc degeneration, and preoperative Oswestry Disability Index (ODI) were screened out from the 43 possible predictors based on LASSO regression. A total of 5 predictors were included while drawing a nomogram of the model. The area under the ROC curve (AUC) value of the model was 0.795. Conclusions: In this study, we successfully developed a good clinical prediction model that can predict the effect of TMD for LDH. A web calculator was designed on the basis of the model (https://fabinlin.shinyapps.io/DynNomapp/).

Mesenchymal stem cell-derived extracellular vesicles therapy in traumatic central nervous system diseases: a systematic review and meta-analysis.

Although there are challenges in treating traumatic central nervous system diseases, mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) have recently proven to be a promising non-cellular therapy. We comprehensively evaluated the efficacy of mesenchymal stem cell-derived extracellular vesicles in traumatic central nervous system diseases in this meta-analysis based on preclinical studies. Our meta-analysis was registered at PROSPERO (CRD42022327904, May 24, 2022). To fully retrieve the most relevant articles, the following databases were thoroughly searched: PubMed, Web of Science, The Cochrane Library, and Ovid-Embase (up to April 1, 2022). The included studies were preclinical studies of mesenchymal stem cell-derived extracellular vesicles for traumatic central nervous system diseases. The Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE)'s risk of bias tool was used to examine the risk of publication bias in animal studies. After screening 2347 studies, 60 studies were included in this study. A meta-analysis was conducted for spinal cord injury (n = 52) and traumatic brain injury (n = 8). The results indicated that mesenchymal stem cell-derived extracellular vesicles treatment prominently promoted motor function recovery in spinal cord injury animals, including rat Basso, Beattie and Bresnahan locomotor rating scale scores (standardized mean difference [SMD]: 2.36, 95% confidence interval [CI]: 1.96-2.76, P < 0.01, I2 = 71%) and mouse Basso Mouse Scale scores (SMD = 2.31, 95% CI: 1.57-3.04, P = 0.01, I2 = 60%) compared with controls. Further, mesenchymal stem cell-derived extracellular vesicles treatment significantly promoted neurological recovery in traumatic brain injury animals, including the modified Neurological Severity Score (SMD = -4.48, 95% CI: -6.12 to -2.84, P < 0.01, I2 = 79%) and Foot Fault Test (SMD = -3.26, 95% CI: -4.09 to -2.42, P = 0.28, I2 = 21%) compared with controls. Subgroup analyses showed that characteristics may be related to the therapeutic effect of mesenchymal stem cell-derived extracellular vesicles. For Basso, Beattie and Bresnahan locomotor rating scale scores, the efficacy of allogeneic mesenchymal stem cell-derived extracellular vesicles was higher than that of xenogeneic mesenchymal stem cell-derived extracellular vesicles (allogeneic: SMD = 2.54, 95% CI: 2.05-3.02, P = 0.0116, I2 = 65.5%; xenogeneic: SMD: 1.78, 95%CI: 1.1-2.45, P = 0.0116, I2 = 74.6%). Mesenchymal stem cell-derived extracellular vesicles separated by ultrafiltration centrifugation combined with density gradient ultracentrifugation (SMD = 3.58, 95% CI: 2.62-4.53, P < 0.0001, I2 = 31%) may be more effective than other EV isolation methods. For mouse Basso Mouse Scale scores, placenta-derived mesenchymal stem cell-derived extracellular vesicles worked better than bone mesenchymal stem cell-derived extracellular vesicles (placenta: SMD = 5.25, 95% CI: 2.45-8.06, P = 0.0421, I2 = 0%; bone marrow: SMD = 1.82, 95% CI: 1.23-2.41, P = 0.0421, I2 = 0%). For modified Neurological Severity Score, bone marrow-derived MSC-EVs worked better than adipose-derived MSC-EVs (bone marrow: SMD = -4.86, 95% CI: -6.66 to -3.06, P = 0.0306, I2 = 81%; adipose: SMD = -2.37, 95% CI: -3.73 to -1.01, P = 0.0306, I2 = 0%). Intravenous administration (SMD = -5.47, 95% CI: -6.98 to -3.97, P = 0.0002, I2 = 53.3%) and dose of administration equal to 100 µg (SMD = -5.47, 95% CI: -6.98 to -3.97, P < 0.0001, I2 = 53.3%) showed better results than other administration routes and doses. The heterogeneity of studies was small, and sensitivity analysis also indicated stable results. Last, the methodological quality of all trials was mostly satisfactory. In conclusion, in the treatment of traumatic central nervous system diseases, mesenchymal stem cell-derived extracellular vesicles may play a crucial role in promoting motor function recovery.

Efficacy of extracellular vesicles of different cell origins in traumatic brain injury: A systematic review and network meta-analysis.

Background: There was still no effective treatment for traumatic brain injury (TBI). Recently, many preclinical studies had shown promising efficacy of extracellular vesicles (EVs) from various cell sources. Our aim was to compare which cell-derived EVs were most effective in treating TBI through a network meta-analysis. Methods: We searched four databases and screened various cell-derived EVs for use in preclinical studies of TBI treatment. A systematic review and network meta-analysis were conducted for two outcome indicators, modified Neurological Severity Score (mNSS) and Morris Water Maze (MWM), and they were ranked by the surface under the cumulative ranking curves (SUCRA). Bias risk assessment was performed with SYRCLE. R software (version 4.1.3, Boston, MA, USA) was used for data analysis. Results: A total of 20 studies were included in this study, involving 383 animals. Astrocyte-derived extracellular vesicles (AEVs) ranked first in response to mNSS at day 1 (SUCRA: 0.26%), day 3 (SUCRA: 16.32%), and day 7 (SUCRA: 9.64%) post-TBI. Extracellular vesicles derived from mesenchymal stem cells (MSCEVs) were most effective in mNSS assessment on day 14 (SUCRA: 21.94%) and day 28 (SUCRA: 6.26%), as well as MWM's escape latency (SUCRA: 6.16%) and time spent in the target quadrant (SUCRA: 86.52%). The result of mNSS analysis on day 21 showed that neural stem cell-derived extracellular vesicles (NSCEVs) had the best curative effect (SUCRA: 6.76%). Conclusion: AEVs may be the best choice to improve early mNSS recovery after TBI. The efficacy of MSCEVs may be the best in the late mNSS and MWM after TBI. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023377350.