Search

ObjectiveWe analyzed the longitudinal profile of Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers in early Parkinson's disease (PD) compared with healthy controls (HCs) and tested baseline CSF biomarkers for prediction of clinical decline in PD.MethodsAmyloid-β 1 to 42 (Aβ42 ), total tau (t-tau) and phosphorylated tau (p-tau) at the threonine 181 position were measured using the high-precision Roche Elecsys electrochemiluminescence immunoassay in all available CSF samples from longitudinally studied patients with PD (n = 416) and HCs (n = 192) followed for up to 3 years in the Parkinson's Progression Markers Initiative (PPMI). Longitudinal CSF and clinical data were analyzed with linear-mixed effects models.ResultsWe found patients with PD had lower CSF t-tau (median = 157.7 pg/mL; range = 80.9-467.0); p-tau (median = 13.4 pg/mL; range = 8.0-40.1), and Aβ42 (median = 846.2 pg/mL; range = 238.8-3,707.0) than HCs at baseline (CSF t-tau median = 173.5 pg/mL; range = 82.0-580.8; p-tau median = 15.4 pg/mL; range = 8.1-73.6; and Aβ42 median = 926.5 pg/mL; range = 239.1-3,297.0; p

Sarcopenia, the age-related decline in muscle mass and function, poses a significant health challenge as the global population ages. Mitochondrial dysfunction is a key factor in sarcopenia, as evidenced by the role of mitochondrial reactive oxygen species (mtROS) in mitochondrial biogenesis and dynamics, as well as mitophagy. Resistance exercise training (RET) is a well-established intervention for sarcopenia; however, its effects on the mitochondria in aging skeletal muscles remain unclear. This review aims to elucidate the relationship between mitochondrial dynamics and sarcopenia, with a specific focus on the implications of RET. Although aerobic exercise training (AET) has traditionally been viewed as more effective for mitochondrial enhancement, emerging evidence suggests that RET may also confer beneficial effects. Here, we highlight the potential of RET to modulate mtROS, drive mitochondrial biogenesis, optimize mitochondrial dynamics, and promote mitophagy in aging skeletal muscles. Understanding this interplay offers insights for combating sarcopenia and preserving skeletal muscle health in aging individuals. [ABSTRACT FROM AUTHOR]

ObjectivesTo assess the neurobiological substrate of initial cognitive decline in Parkinson's disease (PD) to inform patient management, clinical trial design, and development of treatments.MethodsWe longitudinally assessed, up to 3 years, 423 newly diagnosed patients with idiopathic PD, untreated at baseline, from 33 international movement disorder centers. Study outcomes were four determinations of cognitive impairment or decline, and biomarker predictors were baseline dopamine transporter (DAT) single photon emission computed tomography (SPECT) scan, structural magnetic resonance imaging (MRI; volume and thickness), diffusion tensor imaging (mean diffusivity and fractional anisotropy), cerebrospinal fluid (CSF; amyloid beta [Aβ], tau and alpha synuclein), and 11 single nucleotide polymorphisms (SNPs) previously associated with PD cognition. Additionally, longitudinal structural MRI and DAT scan data were included. Univariate analyses were run initially, with false discovery rate = 0.2, to select biomarker variables for inclusion in multivariable longitudinal mixed-effect models.ResultsBy year 3, cognitive impairment was diagnosed in 15-38% participants depending on the criteria applied. Biomarkers, some longitudinal, predicting cognitive impairment in multivariable models were: (1) dopamine deficiency (decreased caudate and putamen DAT availability); (2) diffuse, cortical decreased brain volume or thickness (frontal, temporal, parietal, and occipital lobe regions); (3) co-morbid Alzheimer's disease Aβ amyloid pathology (lower CSF Aβ 1-42); and (4) genes (COMT val/val and BDNF val/val genotypes).ConclusionsCognitive impairment in PD increases in frequency 50-200% in the first several years of disease, and is independently predicted by biomarker changes related to nigrostriatal or cortical dopaminergic deficits, global atrophy due to possible widespread effects of neurodegenerative disease, co-morbid Alzheimer's disease plaque pathology, and genetic factors.

The development of biomarkers to predict the progression of Parkinson's disease (PD) from its earliest stage through its heterogeneous course is critical for research and therapeutic development. The Parkinson's Progression Markers Initiative (PPMI) study is an ongoing international multicenter, prospective study to validate biomarkers in drug-naïve PD patients and matched healthy controls (HC). We quantified cerebrospinal fluid (CSF) alpha-synuclein (α-syn), amyloid-beta1-42 (Aβ1-42), total tau (t-tau), and tau phosphorylated at Thr181 (p-tau) in 660 PPMI subjects at baseline, and correlated these data with measures of the clinical features of these subjects. We found that CSF α-syn, t-tau and p-tau levels, but not Aβ1-42, were significantly lower in PD compared with HC, while the diagnostic value of the individual CSF biomarkers for PD diagnosis was limited due to large overlap. The level of α-syn, but not other biomarkers, was significantly lower in PD patients with non-tremor-dominant phenotype compared with tremor-dominant phenotype. In addition, in PD patients the lowest Aβ1-42, or highest t-tau/Aβ1-42 and t-tau/α-syn quintile in PD patients were associated with more severe non-motor dysfunction compared with the highest or lowest quintiles, respectively. In a multivariate regression model, lower α-syn was significantly associated with worse cognitive test performance. APOE ε4 genotype was associated with lower levels of Aβ1-42, but neither with PD diagnosis nor cognition. Our data suggest that the measurement of CSF biomarkers in early-stage PD patients may relate to disease heterogeneity seen in PD. Longitudinal observations in PPMI subjects are needed to define their prognostic performance.

IntroductionWe describe Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core progress including: the Biobank; cerebrospinal fluid (CSF) amyloid beta (Aβ1-42), t-tau, and p-tau181 analytical performance, definition of Alzheimer's disease (AD) profile for plaque, and tangle burden detection and increased risk for progression to AD; AD disease heterogeneity; progress in standardization; and new studies using ADNI biofluids.MethodsReview publications authored or coauthored by ADNI Biomarker core faculty and selected non-ADNI studies to deepen the understanding and interpretation of CSF Aβ1-42, t-tau, and p-tau181 data.ResultsCSF AD biomarker measurements with the qualified AlzBio3 immunoassay detects neuropathologic AD hallmarks in preclinical and prodromal disease stages, based on CSF studies in non-ADNI living subjects followed by the autopsy confirmation of AD. Collaboration across ADNI cores generated the temporal ordering model of AD biomarkers varying across individuals because of genetic/environmental factors that increase/decrease resilience to AD pathologies.DiscussionFurther studies will refine this model and enable the use of biomarkers studied in ADNI clinically and in disease-modifying therapeutic trials.

Lactate (LA), an endogenous metabolite produced from pyruvate, can accumulate in skeletal muscle in certain conditions including major diseases, as well as during intensive exercise. Using differentiated C2C12 myotubes, we evaluated the early (1-h) and delayed (24-h) effects of LA (8 mM) on mechanisms involved in myogenesis or muscle atrophy, including 5'-adenosine monophosphate-activated protein kinase (AMPK)-mediated inhibition of protein synthesis through the mTOR/P70-S6K pathway, Akt-mediated inhibition of expression of the MAFbx atrophic factor by FOXO3a and expression of the myogenic transcription factors, MyoD, myogenin and myosin heavy chain. Although the early effects of LA overload were not significant on myogenic or atrophic mechanisms, LA treatment for 24 h significantly activated atrophic mechanisms but suppressed myogenesis in myotubes. In addition, LA overload for 24 h significantly suppressed the expression of Sirtuin 1 and peroxisome proliferator-activated receptor gamma coactivator-1 alpha. Consistent with LA-induced activation of atrophic mechanisms, the diameter of C2C12 myotubes treated with LA for 24 h, but not for 1 h, was significantly lower than in control myotubes. Thus, a sustained, but not a transient, LA overload could induce muscle atrophy through the regulation of AMPK- and Akt-mediated pathways, although further in vivo studies are needed to confirm this.

ImportanceWe observed a significant correlation between cerebrospinal fluid (CSF) levels of tau proteins and α-synuclein, but not β-amyloid 1-42 (Aβ1-42), and lower concentration of CSF biomarkers, as compared with healthy controls, in a cohort of entirely untreated patients with Parkinson disease (PD) at the earliest stage of the disease studied so far.ObjectiveTo evaluate the baseline characteristics and relationship to clinical features of CSF biomarkers (Aβ1-42, total tau [T-tau], tau phosphorylated at threonine 181 [P-tau181], and α-synuclein) in drug-naive patients with early PD and demographically matched healthy controls enrolled in the Parkinson's Progression Markers Initiative (PPMI) study.Design, setting, and participantsCross-sectional study of the initial 102 research volunteers (63 patients with PD and 39 healthy controls) of the PPMI cohort.Main outcomes and measuresThe CSF biomarkers were measured by INNO-BIA AlzBio3 immunoassay (Aβ1-42, T-tau, and P-tau181; Innogenetics Inc) or by enzyme-linked immunosorbent assay (α-synuclein). Clinical features including diagnosis, demographic characteristics, motor, neuropsychiatric, and cognitive assessments, and DaTscan were systematically assessed according to the PPMI study protocol.ResultsSlightly, but significantly, lower levels of Aβ1-42, T-tau, P-tau181, α-synuclein, and T-tau/Aβ1-42 were seen in subjects with PD compared with healthy controls but with a marked overlap between groups. Using multivariate regression analysis, we found that lower Aβ1-42 and P-tau181 levels were associated with PD diagnosis and that decreased CSF T-tau and α-synuclein were associated with increased motor severity. Notably, when we classified patients with PD by their motor phenotypes, lower CSF Aβ1-42 and P-tau181 concentrations were associated with the postural instability-gait disturbance-dominant phenotype but not with the tremor-dominant or intermediate phenotype. Finally, we found a significant correlation of the levels of α-synuclein with the levels of T-tau and P-tau181.Conclusions and relevanceIn this first report of CSF biomarkers in PPMI study subjects,we found that measures of CSF Aβ1-42, T-tau, P-tau181, and α-synuclein have prognostic and diagnostic potential in early-stage PD. Further investigations using the entire PPMI cohort will test the predictive performance of CSF biomarkers for PD progression

Objectives This study aimed to develop a robust and accurate deep learning network for detecting the posterior superior alveolar artery (PSAA) in dental cone-beam CT (CBCT) images, focusing on the precise localization of the centre pixel as a critical centreline pixel. Methods PSAA locations were manually labelled on dental CBCT data from 150 subjects. The left maxillary sinus images were horizontally flipped. In total, 300 datasets were created. Six different deep learning networks were trained, including 3D U-Net, deeply supervised 3D U-Net (3D U-Net DS), multi-scale deeply supervised 3D U-Net (3D U-Net MSDS), 3D Attention U-Net, 3D V-Net, and 3D Dense U-Net. The performance evaluation involved predicting the centre pixel of the PSAA. This was assessed using mean absolute error (MAE), mean radial error (MRE), and successful detection rate (SDR). Results The 3D U-Net MSDS achieved the best prediction performance among the tested networks, with an MAE measurement of 0.696 ± 1.552 mm and MRE of 1.101 ± 2.270 mm. In comparison, the 3D U-Net showed the lowest performance. The 3D U-Net MSDS demonstrated a SDR of 95% within a 2 mm MAE. This was a significantly higher result than other networks that achieved a detection rate of over 80%. Conclusions This study presents a robust deep learning network for accurate PSAA detection in dental CBCT images, emphasizing precise centre pixel localization. The method achieves high accuracy in locating small vessels, such as the PSAA, and has the potential to enhance detection accuracy and efficiency, thus impacting oral and maxillofacial surgery planning and decision-making. [ABSTRACT FROM AUTHOR]