Background: Automated and accurate assessment for postural abnormalities is necessary to monitor the clinical progress of Parkinson’s disease (PD). The combination of depth camera and machine learning makes this purpose possible. Methods: Kinect was used to collect the postural images from 70 PD patients. The collected images were processed to extract three-dimensional body joints, which were then converted to two-dimensional body joints to obtain eight quantified coronal and sagittal features (F1-F8) of the trunk. The decision tree classifier was carried out over a data set established by the collected features and the corresponding doctors’ MDS-UPDRS-III 3.13 (the 13th item of the third part of Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale) scores. An objective function was implanted to further improve the human–machine consistency. Results: The automated grading of postural abnormalities for PD patients was realized with only six selected features. The intraclass correlation coefficient (ICC) between the machine’s and doctors’ score was 0.940 (95%CI, 0.905–0.962), meaning the machine was highly consistent with the doctors’ judgement. Besides, the decision tree classifier performed outstandingly, reaching 90.0% of accuracy, 95.7% of specificity and 89.1% of sensitivity in rating postural severity. Conclusions: We developed an intelligent evaluation system to provide accurate and automated assessment of trunk postural abnormalities in PD patients. This study demonstrates the practicability of our proposed method in the clinical scenario to help making the medical decision about PD.

Postural abnormalities are common disabling motor complications affecting patients with Parkinson’s disease (PD). We proposed a summary index for postural abnormalities (IPA) based on Kinect depth camera and explored the clinical value of this indicator. Seventy individuals with PD and thirty age-matched healthy controls (HCs) were enrolled. All participants were tested using a Kinect-based system with IPA automatically obtained by algorithms. Significant correlations were detected between IPA and the Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) total score (r_s = 0.369, p = 0.002), MDS-UPDRS-III total score (r_s = 0.431, p < 0.001), MDS-UPDRS-III 3.13 score (r_s = 0.573, p < 0.001), MDS-UPDRS-III-bradykinesia score (r_s = 0.311, p = 0.010), the 39-item Parkinson’s Disease Questionnaire (PDQ-39) (r_s = 0.272, p = 0.0027) and the Berg Balance Scale (BBS) score (r_s = −0.350, p = 0.006). The optimal cut-off value of IPA for distinguishing PD from HCs was 12.96 with a sensitivity of 97.14%, specificity of 100.00%, area under the curve (AUC) of 0.999 (0.997–1.002, p < 0.001), and adjusted AUC of 0.998 (0.993–1.000, p < 0.001). The optimal cut-off value of IPA for distinguishing between PD with and without postural abnormalities was 20.14 with a sensitivity, specificity, AUC and adjusted AUC of 77.78%, 73.53%, 0.817 (0.720–0.914, p < 0.001), and 0.783 (0.631–0.900, p < 0.001), respectively. IPA was significantly correlated to the clinical manifestations of PD patients, and could reflect the global severity of postural abnormalities in PD with important value in distinguishing PD from HCs and distinguishing PD with postural abnormalities from those without.

Dyskinesia is one of the most disabling motor complications in Parkinson’s Disease (PD). Sleep is crucial to keep neural circuit homeostasis, and PD patients often suffer from sleep disturbance. However, few prospective studies have been conducted to investigate the association of sleep quality with dyskinesia in PD. The objective of the current study is to investigate the association between sleep quality and dyskinesia and build a prediction model for dyskinesia in PD. We prospectively followed a group of PD patients without dyskinesia at baseline for a maximum of 36 months. Univariable and multivariable Cox regression with stepwise variable selection was used to investigate risk factors for dyskinesia. The performance of the model was assessed by the time-dependent area under the receiver-operating characteristic curve (AUC). At the end of follow-up, 32.8% of patients developed dyskinesia. Patients with bad sleep quality had a significantly higher proportion of dyskinesia compared with those with good sleep quality (48.1% vs. 20.6%, p = 0.023). Multivariable Cox regression selected duration of PD, sleep quality, cognition, mood, and levodopa dose. Notably, high Pittsburgh sleep quality index (PSQI) score was independently associated with an increased risk of dyskinesia (HR = 2.96, 95% CI 1.05–8.35, p = 0.041). The model achieved a good discriminative ability, with the highest AUC being 0.83 at 35 months. Our results indicated that high PSQI score may increase the risk of developing dyskinesia in PD, implying that therapeutic intervention targeting improving sleep quality may be a promising approach to prevent or delay the development of dyskinesia in PD.

Primary peripheral nerve sheath tumors (PNSTs) of the thyroid gland are rare, with fewer than 30 cases reported in the medical literature to date. Primary PNSTs of the thyroid gland are classified into malignant and benign PNSTs. The benign PNSTs may be further subclassified into neurofibromas and schwannomas. This is the case report of a 51-year-old male patient presenting with multiple primary PNSTs involving the left lobe of the thyroid gland. The patient underwent total excision of the thyroid gland and the pathological results indicated a schwannoma with Antoni type A and B cells. The literature was reviewed briefly and, to the best of our knowledge, this is the first case report of multiple primary PNSTs of the thyroid gland.

Progressive accumulation of misfolded SNCA/α‐synuclein is key to the pathology of Parkinson’s disease (PD). Drugs aiming at degrading SNCA may be an efficient therapeutic strategy for PD. Our previous study showed that mesencephalic astrocyte‐derived neurotrophic factor (MANF) facilitated the removal of misfolded SNCA and rescued dopaminergic (DA) neurons, but the underlying mechanisms remain unknown. In this study, we showed that AAV8‐MANF relieved Parkinsonian behavior in rotenone‐induced PD model and reduced SNCA accumulation in the substantia nigra. By establishing wildtype (WT) SNCA overexpression cellular model, we found that chaperone‐mediated‐autophagy (CMA) and macroautophagy were both participated in MANF‐mediated degradation of SNCA^WT. Nuclear factor erythroid 2‐related factor (Nrf2) was activated to stimulating macroautophagy activity when CMA pathway was impaired. Using A53T mutant SNCA overexpression cellular model to mimic CMA dysfunction situation, we concluded that macroautophagy rather than CMA was responsible to the degradation of SNCA^A53T, and this degradation was mediated by Nrf2 activation. Hence, our findings suggested that MANF has potential therapeutic value for PD. Nrf2 and its role in MANF‐mediated degradation may provide new sights that target degradation pathways to counteract SNCA pathology in PD.

Botulinum toxin type-A (Btx-A), a powerful therapeutic tool in various medical specialties, requires repeated injections to maintain its effect. Therefore, novel methods to prolong the effective duration time of Btx-A are highly needed. Rats were assigned to three major groups: control group (n = 30), Btx-A group (n = 30), and IGF-1 Ab groups. IGF-1 Ab groups were composed by sub-groups A1–A5 (each has 25 rats) for the subsequent IGF-1Ab dose-effect study. Muscle strength was determined by a survey system for rat lower limbs nerve and muscle function. Muscle-specific receptor tyrosine kinase (MuSK), Insulin-like growth factor binding protein-5 (IGFBP5), and growth-associated protein, 43-kDa (GAP43) were determined by real-time polymerase chain reactions (PCRs) and Western blot. We found that Btx-A decreased the muscle strength, with a paralysis maintained for 70 days. IGF-1Ab prolonged the effective duration time of Btx-A. Real-time PCRs and Western blot showed that IGF-1Ab delayed the increase of MuSK and IGFBP5 after Btx-A injection, without affecting GAP43. These results indicate that IGF-1Ab might prolong the effective duration time of Btx-A on muscle strength through delaying the increase of MuSK. It would be interesting to determine whether IGF-1Ab can be used as an auxiliary measure to the Btx-A treatment in the future.