Decreased cerebrospinal fluid orexin levels not associated with clinical sleep disturbance in Parkinson's disease: A retrospective study.

Patients with Parkinson's disease (PD) often suffer from sleep disturbances, including excessive daytime sleepiness (EDS) and rapid eye movement sleep behavior disorder (RBD). These symptoms are also experienced by patients with narcolepsy, which is characterized by orexin neuronal loss. In PD, a decrease in orexin neurons is observed pathologically, but the association between sleep disturbance in PD and cerebrospinal fluid (CSF) orexin levels is still unclear. This study aimed to clarify the role of orexin as a biomarker in patients with PD. CSF samples were obtained from a previous cohort study conducted between 2015 and 2020. We cross-sectionally and longitudinally examined the association between CSF orexin levels, sleep, and clinical characteristics. We analyzed 78 CSF samples from 58 patients with PD and 21 samples from controls. CSF orexin levels in patients with PD (median = 272.0 [interquartile range = 221.7-334.5] pg/mL) were lower than those in controls (352.2 [296.2-399.5] pg/mL, p = 0.007). There were no significant differences in CSF orexin levels according to EDS, RBD, or the use of dopamine agonists. Moreover, no significant correlation was observed between CSF orexin levels and clinical characteristics by multiple linear regression analysis. Furthermore, the longitudinal changes in orexin levels were also not correlated with clinical characteristics. This study showed decreased CSF orexin levels in patients with PD, but these levels did not show any correlation with any clinical characteristics. Our results suggest the limited efficacy of CSF orexin levels as a biomarker for PD, and that sleep disturbances may also be affected by dysfunction of the nervous system other than orexin, or by dopaminergic treatments in PD. Understanding the reciprocal role of orexin among other neurotransmitters may provide a better treatment strategy for sleep disturbance in patients with PD

Successful Reboot of High-Performance Sporting Activities by Japanese National Women’s Handball Team in Tokyo, 2020 during the COVID-19 Pandemic: An Initiative Using the Japan Sports–Cyber Physical System (JS–CPS) of the Sports Research Innovation Project (SRIP)

The COVID-19 pandemic has negatively impacted sporting activities across the world. However, practical training strategies for athletes to reduce the risk of infection during the pandemic have not been definitively studied. The purpose of this report was to provide an overview of the challenges we encountered during the reboot of high-performance sporting activities of the Japanese national handball team during the 3rd wave of the COVID-19 pandemic in Tokyo, Japan. Twenty-nine Japanese national women’s handball players and 24 staff participated in the study. To initiate the reboot of their first training camp after COVID-19 stay-home social policy, we conducted: web-based health-monitoring, SARS-CoV-2 screening with polymerase chain reaction (PCR) tests, real-time automated quantitative monitoring of social distancing on court using a moving image-based artificial intelligence (AI) algorithm, physical intensity evaluation with wearable heart rate (HR) and acceleration sensors, and a self-reported online questionnaire. The training camp was conducted successfully with no COVID-19 infections. The web-based health monitoring and the frequent PCR testing with short turnaround times contributed remarkably to early detection of athletes’ health problems and to risk screening. During handball, AI-based on-court social-distance monitoring revealed key time-dependent spatial metrics to define player-to-player proximity. This information facilitated appropriate on- and off-game distancing behavior for teammates. Athletes regularly achieved around 80% of maximum HR during training, indicating anticipated improvements in achieving their physical intensities. Self-reported questionnaires related to the COVID management in the training camp revealed a sense of security among the athletes that allowed them to focus singularly on their training. The challenges discussed herein provided us considerable knowledge about creating and managing a safe environment for high-performing athletes in the COVID-19 pandemic via the Japan Sports–Cyber Physical System (JS–CPS) of the Sports Research Innovation Project (SRIP, Japan Sports Agency, Tokyo, Japan). This report is envisioned to provide informed decisions to coaches, trainers, policymakers from the sports federations in creating targeted, infection-free, sporting and training environments

Visual rating of TTP/ASL.

<p>Results of the visual qualitative analysis. As hypoperfusion in ASL occurred exclusively as part of ATDA and not isolated, for ASL only the categories ATDA and normal are presented.</p><p>Rows show imaging findings for ASL-CBF, columns show imaging findings for DSC-TTP. Patients rated uninterpretable were excluded. Of 14 patients with a TTP delay, 10 showed Arterial Transit Delay Artifacts in ASL (specificity: 71%; false negative rate: 29%). Out of 3 patients with normal findings in TTP, 1 showed ATDAs in ASL (false positive rate: 67%).</p><p>DSC-TTP: Dynamic Susceptibility Contrast - Time to Peak; ASL: Arterial Spin Labeling; ATDA: Arterial Transit Delay Artifact.</p

Clinical data of all patients.

<p>y: years; p: points; mRS: Modified Rankin Scale, NIHSS: National Institute of Health Stroke Scale; GoS: Grade of Stenosis; ICA: Internal Carotid Artery; MCA: Middle Cerebral Artery.</p

Visual rating of DSC-CBF/ASL.

<p>Results of the visual qualitative analysis. As hypoperfusion in ASL occurred exclusively as part of ATDA and not isolated, for ASL only the categories ATDA and normal are presented.</p><p>Rows show imaging findings for ASL-CBF, columns show imaging findings for DSC-CBF. Patients rated uninterpretable were excluded.</p><p>Of 11 patients with hypoperfusion in DSC-CBF, 9 patients showed ATDAs in ASL (specificity: 82%; false negative rate: 18%). 6 patients had normal DSC-CBF findings, 3 of them showed ATDAs in ASL (false positive: 50%).</p><p>DSC-CBF: Dynamic Susceptibility Contrast - Cerebral Blood Flow; ASL: Arterial Spin Labeling; ATDA: Arterial Transit Delay Artifact.</p

Scatter plots comparing DSC-relCBF and ASL-relCBF (A) and relTTP and ASL-relCBF (B).

<p>Pooled data of 17 patients. The diversity of the results is demonstrated in the two scatter plots. Spearman‘s rho for the pooled data was r = 0,24 (p<0,05) for DSC-relCBF vs ASL-relCBF and r = −0,32 (p<0,05) for relTTP vs ASL-relCBF.</p

Arterial Transit Delay Artifact.

<p>Origin of the Arterial Transit Delay Artifact in ASL (labeling slice = green, imaging slices = blue). If arterial transit time is prolonged as it is the case in our patients, the inflow time is too short. Imaging slices capture high signal of labeled blood that is still in small arteries (as indicated by hyperintensities inside the labeling slices; red arrow) and hypointense areas, which the labeled blood has not yet reached. In parts of the brain where the arterial transit time is normal, blood has already exchanged with residual water and the ASL image appears normal (white arrow).</p

Exemplary patients showing blood arrival delay effects in ASL imaging.

<p>A) 66-year-old female, occlusion of the right ICA. The TTP image shows a visible ipsilateral delay (relTTP = 0.8 sec). In the ASL image, hyperintense arterial transit delay artifacts are seen (small white arrows). On the reference DSC-CBF map, a hypoperfusion in the affected hemisphere is present. B) 45-year-old female, occlusion of the left middle cerebral artery. In the ASL image, a hypointensity is seen in the area affected by delay (large white arrow, relTTP = 1.5 sec). In contrast, no apparent changes are present in the DSC-CBF map. In patient A, a moderate blood transit delay leads to the presence of hyperintense ADTA. The more severe delay in patient B might explain the hypointense ADTA surrounded by hyperintense areas in its borderzone as a sign of collateral macrovessels. All slices are coregistered. The scales do not represent absolute values.</p

Quantitative analysis of DSC-CBF, DSC-TTP and ASL-relCBF.

<p>20(ROIs) were placed on the FLAIR image and copied onto coregistered DSC-CBF, DSC-TTP and ASL images. For relative values, the ratio of each ipsilateral ROI to the arithmetic mean of all contralateral ROIs was calculated. In case of DSC-TTP the values were subtracted to obtain relative TTP-delay. DSC-perfusion maps were automatically masked by the used software. Therefore, the contour of DSC maps was used to define the cortical rim (contour, arrows).</p