The α-synuclein seed amplification assay: Interpreting a test of Parkinson's pathology.

The α-synuclein seed amplification assay (αSyn-SAA) sensitively detects Lewy pathology, the amyloid state of α-synuclein, in the cerebrospinal fluid (CSF) of patients with Parkinson's disease (PD). The αSyn-SAA harnesses the physics of seeding, whereby a superconcentrated solution of recombinant α-synuclein lowers the thermodynamic threshold (nucleation barrier) for aggregated α-synuclein to act as a nucleation catalyst ("seed") to trigger the precipitation (nucleation) of monomeric α-synuclein into pathology. This laboratory setup increases the signal for identifying a catalyst if one is present in the tissue examined.

Is rapid eye movement sleep behavior disorder a marker of Parkinson's disease severity?

Background: Parkinson's disease (PD) is characterized by motor and non-motor features. There are several proposed clinical markers to define disease severity. However, if rapid eye movement sleep behavior disorder (RBD) is associated with worse prognosis of both motor and non-motor findings in PD is unknown.

Modeling, evaluation and metrics performance of the SyncLMKD in distributed kinematics variations.

Modeling the Digital Twin (DT) is an important resource for accurately representing the physical entity, enabling it to deliver functional services, meet application requirements, and address the disturbances between the physical and digital realms. This article introduces the Log Mean Kinematics Difference Synchronization (SyncLMKD) to measure the kinematic variations distributed among Digital Twin elements to ensure symmetric values relative to a reference. The proposed method employs abductive reasoning and draws inspiration from the Log Mean Temperature Difference (LMTD).

The impact on productivity costs of reducing unemployment in patients with advanced breast cancer: A model estimation based on a Portuguese nationwide observational study.

This study aimed to characterize the employment status and work-related conditions of patients with advanced breast cancer (ABC) in Portugal and quantify the productivity costs of premature abandonment of the work market while evaluating strategies to promote employment. The analysis was based on a cumulative incidence model for estimation of ABC prevalence and on a cross-sectional study characterizing the employment status of patients with ABC. This study was conducted in Portuguese hospitals, between Nov2021-Dec2022 and included patients diagnosed with ABC for at least 6 months, aged 66 or less and consenting for a self-answered questionnaire regarding work status.