@article{PozziBolzoniBiellaetal.2023, author = {Pozzi, Nicol{\´o} Gabriele and Bolzoni, Francesco and Biella, Gabriele Eliseo Mario and Pezzoli, Gianni and Ip, Chi Wang and Volkmann, Jens and Cavallari, Paolo and Asan, Esther and Isaias, Ioannis Ugo}, title = {Brain noradrenergic innervation supports the development of Parkinson's tremor: a study in a reserpinized rat model}, series = {Cells}, volume = {12}, journal = {Cells}, number = {21}, issn = {2073-4409}, doi = {10.3390/cells12212529}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-357721}, year = {2023}, abstract = {The pathophysiology of tremor in Parkinson's disease (PD) is evolving towards a complex alteration to monoaminergic innervation, and increasing evidence suggests a key role of the locus coeruleus noradrenergic system (LC-NA). However, the difficulties in imaging LC-NA in patients challenge its direct investigation. To this end, we studied the development of tremor in a reserpinized rat model of PD, with or without a selective lesioning of LC-NA innervation with the neurotoxin DSP-4. Eight male rats (Sprague Dawley) received DSP-4 (50 mg/kg) two weeks prior to reserpine injection (10 mg/kg) (DR-group), while seven male animals received only reserpine treatment (R-group). Tremor, rigidity, hypokinesia, postural flexion and postural immobility were scored before and after 20, 40, 60, 80, 120 and 180 min of reserpine injection. Tremor was assessed visually and with accelerometers. The injection of DSP-4 induced a severe reduction in LC-NA terminal axons (DR-group: 0.024 ± 0.01 vs. R-group: 0.27 ± 0.04 axons/um\(^2\), p < 0.001) and was associated with significantly less tremor, as compared to the R-group (peak tremor score, DR-group: 0.5 ± 0.8 vs. R-group: 1.6 ± 0.5; p < 0.01). Kinematic measurement confirmed the clinical data (tremor consistency (\% of tremor during 180 s recording), DR-group: 37.9 ± 35.8 vs. R-group: 69.3 ± 29.6; p < 0.05). Akinetic-rigid symptoms did not differ between the DR- and R-groups. Our results provide preliminary causal evidence for a critical role of LC-NA innervation in the development of PD tremor and foster the development of targeted therapies for PD patients.}, language = {en} } @article{HaufeIsaiasPellegrinietal.2023, author = {Haufe, Stefan and Isaias, Ioannis U. and Pellegrini, Franziska and Palmisano, Chiara}, title = {Gait event prediction using surface electromyography in parkinsonian patients}, series = {Bioengineering}, volume = {10}, journal = {Bioengineering}, number = {2}, issn = {2306-5354}, doi = {10.3390/bioengineering10020212}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-304380}, year = {2023}, abstract = {Gait disturbances are common manifestations of Parkinson's disease (PD), with unmet therapeutic needs. Inertial measurement units (IMUs) are capable of monitoring gait, but they lack neurophysiological information that may be crucial for studying gait disturbances in these patients. Here, we present a machine learning approach to approximate IMU angular velocity profiles and subsequently gait events using electromyographic (EMG) channels during overground walking in patients with PD. We recorded six parkinsonian patients while they walked for at least three minutes. Patient-agnostic regression models were trained on temporally embedded EMG time series of different combinations of up to five leg muscles bilaterally (i.e., tibialis anterior, soleus, gastrocnemius medialis, gastrocnemius lateralis, and vastus lateralis). Gait events could be detected with high temporal precision (median displacement of <50 ms), low numbers of missed events (<2\%), and next to no false-positive event detections (<0.1\%). Swing and stance phases could thus be determined with high fidelity (median F1-score of ~0.9). Interestingly, the best performance was obtained using as few as two EMG probes placed on the left and right vastus lateralis. Our results demonstrate the practical utility of the proposed EMG-based system for gait event prediction, which allows the simultaneous acquisition of an electromyographic signal to be performed. This gait analysis approach has the potential to make additional measurement devices such as IMUs and force plates less essential, thereby reducing financial and preparation overheads and discomfort factors in gait studies.}, language = {en} } @article{GrotemeyerFischerKoprichetal.2023, author = {Grotemeyer, Alexander and Fischer, Judith F. and Koprich, James B. and Brotchie, Jonathan M. and Blum, Robert and Volkmann, Jens and Ip, Chi Wang}, title = {Inflammasome inhibition protects dopaminergic neurons from α-synuclein pathology in a model of progressive Parkinson's disease}, series = {Journal of Neuroinflammation}, volume = {20}, journal = {Journal of Neuroinflammation}, doi = {10.1186/s12974-023-02759-0}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-357652}, year = {2023}, abstract = {Neuroinflammation has been suggested as a pathogenetic mechanism contributing to Parkinson's disease (PD). However, anti-inflammatory treatment strategies have not yet been established as a therapeutic option for PD patients. We have used a human α-synuclein mouse model of progressive PD to examine the anti-inflammatory and neuroprotective effects of inflammasome inhibition on dopaminergic (DA) neurons in the substantia nigra (SN). As the NLRP3 (NOD-, LRR- and pyrin domain-containing 3)-inflammasome is a core interface for both adaptive and innate inflammation and is also highly druggable, we investigated the implications of its inhibition. Repeat administration of MCC950, an inhibitor of NLRP3, in a PD model with ongoing pathology reduced CD4\(^+\) and CD8\(^+\) T cell infiltration into the SN. Furthermore, the anti-inflammasome treatment mitigated microglial activation and modified the aggregation of α-synuclein protein in DA neurons. MCC950-treated mice showed significantly less neurodegeneration of DA neurons and a reduction in PD-related motor behavior. In summary, early inflammasome inhibition can reduce neuroinflammation and prevent DA cell death in an α-synuclein mouse model for progressive PD.}, language = {en} }