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Background Dementia is a prevalent non-motor manifestation among individuals with advanced Parkinson’s disease (PD). Glial fibrillary acidic protein (GFAP) is an inflammatory marker derived from astrocytes. Research has demonstrated the potential of plasma GFAP to forecast the progression to dementia in PD patients with mild cognitive impairment (PD–MCI). However, the predictive role of cerebrospinal fluid (CSF) GFAP on future cognitive transformation and alterations in Alzheimer’s disease (AD)-associated CSF biomarkers in newly diagnosed PD patients has not been investigated. Methods 210 de novo PD patients from the Parkinson’s Progression Markers Initiative were recruited. Cognitive progression in PD participants was evaluated using Cox regression. Cross-sectional and longitudinal associations between baseline CSF GFAP and cognitive function and AD-related CSF biomarkers were evaluated using multiple linear regression and generalized linear mixed model. Results At baseline, the mean age of PD participants was 60.85 ± 9.78 years, including 142 patients with normal cognition (PD–NC) and 68 PD–MCI patients. The average follow-up time was 6.42 ± 1.69 years. A positive correlation was observed between baseline CSF GFAP and age (β = 0.918, p < 0.001). There was no statistically significant difference in baseline CSF GFAP levels between PD–NC and PD–MCI groups. Higher baseline CSF GFAP predicted greater global cognitive decline over time in early PD patients (Montreal Cognitive Assessment, β = − 0.013, p = 0.014). Furthermore, Cox regression showed that high baseline CSF GFAP levels were associated with a high risk of developing dementia over an 8-year period in the PD–NC group (adjusted HR = 3.070, 95% CI 1.119–8.418, p = 0.029). In addition, the baseline CSF GFAP was positively correlated with the longitudinal changes of not only CSF α-synuclein (β = 0.313, p < 0.001), but also CSF biomarkers associated with AD, namely, amyloid-β 42 (β = 0.147, p = 0.034), total tau (β = 0.337, p < 0.001) and phosphorylated tau (β = 0.408, p < 0.001). Conclusions CSF GFAP may be a valuable prognostic tool that can predict the severity and progression of cognitive deterioration, accompanied with longitudinal changes in AD-associated pathological markers in early PD.

Welding path planning and motion matching of complex tanks are major areas of research for intelligent welding equipment. In the present work, the welding of tank with variable curvature section was taken as the study object, an innovative method to automatically generate the posture of welding torch at the welding spots of variable curvature section was proposed. The torch posture homogeneous transformation matrix was established, and the equation of welding motion matching on basis of the method of torch posture planning was constructed by combining the angle planning equation of the positioner. Then, a set of welding torch posture and positioner’s rotation angles along the welding path of variable curvature section was created in Matlab, and the combination code of the welding torch movement and positioner rotation was obtained to accurately control the welding speed, wire extension and the posture of welding torch during the welding process of the tank. An aluminum alloy tank composed of eight arcs was chosen to verify the proposed technique. The results show that the difference of welding position at the same positioner’s rotation angle ranged from -0.7976 mm to 0.7616 mm, the repeatability accuracy of the posture of the automatic welding system was less than 0.1 mm, and the weld qualification rate of aluminum alloy tank is more than 98% with limited weld defects. That is, the tanks with variable curvature sections can be automatically and accurately welded by the proposed method.

ObjectivePrevious studies have reported that white matter hyperintensities (WMHs) are associated with freezing of gait (FOG), but it is not clear whether their distribution areas have correlations with FOG in Parkinson’s disease (PD) and the potential influencing factors about WMHs.MethodsTwo hundred and forty-six patients with PD who underwent brain MRI were included. Participants were divided into PD with FOG (n = 111) and PD without FOG (n = 135) groups. Scheltens score was used to assess the WMHs burden in the areas of deep white matter hyperintensities (DWMHs), periventricular hyperintensities (PVHs), basal ganglia hyperintensities (BGHs), and infratentorial foci of hyperintensities (ITF). Whole brain WMHs volume was evaluated by automatic segmentation. Binary logistic regression was used to evaluate relationships between WMHs and FOG. The common cerebrovascular risk factors that may affect WMHs were evaluated by mediation analysis.ResultsThere were no statistical differences between PD with and without FOG groups in whole brain WMHs volume, total Scheltens score, BGHs, and ITF. Binary logistic regression showed that the total scores of DWMHs (OR = 1.094; 95% CI, 1.001, 1.195; p = 0.047), sum scores of PVHs and DWMHs (OR = 1.080; 95% CI, 1.003, 1.164; p = 0.042), especially the DWMHs in frontal (OR = 1.263; 95% CI, 1.060, 1.505 p = 0.009), and PVHs in frontal caps (OR = 2.699; 95% CI, 1.337, 5.450; p = 0.006) were associated with FOG. Age, hypertension, and serum alkaline phosphatase (ALP) are positively correlated with scores of DWMHs in frontal and PVHs in frontal caps.ConclusionThese results indicate that WMHs distribution areas especially in the frontal of DWMHs and PVHs play a role in PD patients with FOG.

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