Journal of Alzheimers Disease & Parkinsonism
Open Access

Parkinsonism presents a diagnostic challenge due to its heterogeneous clinical manifestations, which often overlap with other neurological conditions. However, a comprehensive evaluation led to the diagnosis of Vascular Parkinsonism (VP) based on clinical findings, neuroimaging and response to treatment. The article highlights the importance of a thorough differential diagnosis in Parkinsonism and underscores the role of neuroimaging in distinguishing between idiopathic PD and secondary parkinsonian syndromes.

Parkinsonism encompasses a spectrum of neurological disorders characterized by motor symptoms such as bradykinesia, rigidity, tremor and postural instability. Parkinson's Disease (PD) represents the most common form of parkinsonism, accounting for approximately 85% of cases. However, numerous other conditions, including Vascular Parkinsonism (VP), Multiple System Atrophy (MSA) and Progressive Supranuclear Palsy (PSP) can present with similar clinical features, posing diagnostic challenges for clinicians. Lewy pathology which is caused by the aggregation of α-synuclein i s a pathological sign of Parkinson's Disease (PD). The Lewy pathology refers to abnormal protein deposits primarily composed of alpha-synuclein in the brain. These deposits called Lewy bodies and Lewy neurites, are characteristic features of neurodegenerative disorders like Parkinson's Disease (PD) and Dementia with Lewy Bodies (DLB).

Advancement diagnosis in Parkinson’s disease

Recent years have seen advancements in the optimization of the Parkinson's disease diagnosis procedure notably in the identification of fluid biomarkers. They disrupt normal cellular function, impairing communication between nerve cells and leading to the progressive decline of cognitive and motor abilities. Symptoms include movement difficulties, cognitive impairment, visual hallucinations and fluctuations in alertness. Understanding Lewy pathology is for diagnosing and developing treatments for these debilitating conditions. α-synuclein's position in pre-synaptic nerve terminals implies that it may play a significant role in vesicle trafficking in nerve terminals despite the fact that its normal function is still little understood.

Parkinson's disease biosensors

Most of the studies were able to detect and quantify very low levels of α-synuclein related biomarkers attaining commercial available products such as Enzyme Linked Immuno Sorbent Assay (ELISA). It detects and quantifies proteins, such as antibodies, antigens, hormones and cytokines in a sample. ELISA involves immobilizing a target protein onto a surface, then adding specific antibodies that bind to the target. After washing away unbound substances, an enzyme-linked secondary antibody is applied producing a detectable signal when it binds. The intensity of the signal corresponds to the concentration of the target protein enabling precise measurement. ELISA's sensitivity, specificity and ease of use make it indispensable in medical diagnostics and research. Due to this characteristic they are ideal candidates for the development of diagnostic instruments that can accurately determine this biomarker in biological fluids that are easier to access, such blood where the biomarker's levels are sometimes ten to one hundred times higher.

Parkinsonism poses diagnostic challenges due to its varied etiologies and overlapping clinical features. A comprehensive evaluation, including detailed history-taking, neurological examination and neuroimaging is essential for accurate diagnosis and appropriate management. The study underscores the importance of considering secondary causes of Parkinsonism such as VP, particularly in patients with vascular risk factors or atypical clinical features. Further study is needed to elucidate the pathophysiology of VP and optimize treatment strategies for this condition. Electrochemical impedance spectroscopy is a valuable tool for researchers but presents challenges in conducting experiments and analyzing data. Determining a suitable equivalent circuit to represent the electrochemical system and choosing appropriate data analysis formalisms are key difficulties. Fitting experimental data to these models requires an in-depth understanding of electrochemical processes. To address these challenges, refined equivalent circuit models, advanced data analysis formalisms and simulation-based methods are suggested. Additionally, advancements in measurement techniques, data processing and machine learning algorithms can enhance the accuracy and reliability of impedance analysis, providing deeper insights into electrochemical systems.