Horizontal Pendular Nystagmus and Ataxia Secondary to Severe Hypomagnesemia.

Background: Severe hypomagnesemia is an increasingly recognized cause of acute and reversible cerebellar ataxia, often accompanied by cerebellar oculomotor signs such as jerky horizontal or downbeat nystagmus and very rarely ocular flutter. Phenomenology Shown: This video illustrates horizontal pendular nystagmus in a patient with acute onset cerebellar ataxia associated with severe hypomagnesemia. Educational value: Acquired pendular nystagmus can be distinguished from macrosaccadic oscillations and ocular flutter in that the former is composed of two slow phases of equal velocity and the latter of two fast phases of saccadic type with or without intersaccadic interval, respectively. It is most commonly associated with demyelinating, toxic, metabolic, and genetic disorders, but has not been reported in association with severe hypomagnesemia.

LAM Test: A New Cognitive Marker for Early Detection in Preclinical Alzheimer's Disease.

Background: With the arrival of disease-modifying treatments, it is mandatory to find new cognitive markers that are sensitive to Alzheimer's disease (AD) pathology in preclinical stages. Objective: To determine the utility of a newly developed Learning and Associative Memory face test: LAM test. This study examined the relationship between AD cerebrospinal fluid (CSF) biomarkers and performance on LAM test, and assessed its potential clinical applicability to detect subtle changes in cognitively healthy subjects at risk for AD. Methods: We studied eighty cognitively healthy volunteers from the Valdecilla cohort. 61% were women and the mean age was 67.34 years (±6.416). All participants underwent a lumbar puncture for determination of CSF biomarkers and an extensive neuropsychological assessment, including performance on learning and associative memory indices of the LAM-test after 30 min and after 1 week, and two classic word lists to assess verbal episodic memory: the Rey Auditory Verbal Learning Test (RAVLT) and the Free and Cued Selective Reminding Test (FCSRT). We analyzed cognitive performance according to amyloid status (A+ versus A-) and to ATN model (A-T-N-; A+T-N-; A+T+N-/A+T+N+). Results: Performance on the LAM-test was significantly correlated with CSF Aß ratio. A+ participants performed worse on both learning (mean difference = 2.19, p = 0.002) and memory LAM measures than A- (mean difference = 2.19, p = 0.004). A decline in performance was observed along the Alzheimer's continuum, with significant differences between ATN groups. Conclusions: Our findings suggest that LAM test could be a useful tool for the early detection of subjects within the AD continuum, outperforming classical memory tests.

Oculomotor Dysfunction in Idiopathic and LRRK2-Parkinson's Disease and At-Risk Individuals.

Background: Video-oculography constitutes a highly-sensitive method of characterizing ocular movements, which could detect subtle premotor changes and contribute to the early diagnosis of Parkinson's disease (PD). Objective: To investigate potential oculomotor differences between idiopathic PD (iPD) and PD associated with the G2019S variant of LRRK2 (L2PD), as well as to evaluate oculomotor function in asymptomatic carriers of the G2019S variant of LRRK2. Methods: The study enrolled 129 subjects: 30 PD (16 iPD, 14 L2PD), 23 asymptomatic carriers, 13 non-carrier relatives of L2PD patients, and 63 unrelated HCs. The video-oculographic evaluation included fixation, prosaccade, antisaccade, and memory saccade tests. Results: We did not find significant differences between iPD and L2PD. Compared to controls, PD patients displayed widespread oculomotor deficits including larger microsaccades, hypometric vertical prosaccades, increased latencies in all tests, and lower percentages of successful antisaccades and memory saccades. Non-carrier relatives showed oculomotor changes with parkinsonian features, such as fixation instability and hypometric vertical saccades. Asymptomatic carriers shared multiple similarities with PD, including signs of unstable fixation and hypometric vertical prosaccades; however, they were able to reach percentages of successful antisaccade and memory saccades similar to controls, although at the expense of longer latencies. Classification accuracy of significant oculomotor parameters to differentiate asymptomatic carriers from HCs ranged from 0.68 to 0.74, with BCEA, a marker of global fixation instability, being the parameter with the greatest classification accuracy. Conclusions: iPD and LRRK2-G2019S PD patients do not seem to display a differential oculomotor profile. Several oculomotor changes in asymptomatic carriers of LRRK2 mutations could be considered premotor biomarkers.

CLADSI: Deep Continual Learning for Alzheimer's Disease Stage Identification Using Accelerometer Data.

Alzheimer's disease (AD) is a neurodegenerative disorder that can cause a significant impairment in physical and cognitive functions. Gait disturbances are also reported as a symptom of AD. Previous works have used Convolutional Neural Networks (CNNs) to analyze data provided by motion sensors that monitor Alzheimer's patients. However, these works have not explored continual learning algorithms that allow the CNN to configure itself as it receives new data from these sensors. This work proposes a method aimed at enabling CNNs to learn from a continuous stream of data from motion sensors without having full access to previous data. The CNN identifies the stage of AD from the analysis of data provided by motion sensors. The work includes an experimentation with data captured by accelerometers that monitored the activity of 35 Alzheimer's patients for a week in a daycare center. The CNN achieves an accuracy of 86,94%, 86,48% and 84,37% for 2, 3 and 4 experiences respectively. The proposal provides advantages to working with a continuous stream of data so that the CNN are constantly self-configuring without the intervention of a human. The work can be considered as promising and helpful in finding deep learning solutions in medical cases in which patients are constantly monitored.

Where Should I Draw the Line: PET-Driven, Data-Driven, or Manufacturer Cut-Off?

Background: The optimal cut-off for Alzheimer's disease (AD) CSF biomarkers remains controversial. Objective: To analyze the performance of cut-off points standardized by three methods: one that optimized the agreement between 11C-Pittsburgh compound B PET (a-PET) and CSF biomarkers (Aß1-42, pTau, tTau, and Aß1-42/Aß1-40 ratio) in our population, called PET-driven; an unbiased cut-off using data from a healthy research cohort, called data-driven, and that provided by the manufacturer. We also compare changes in ATN classification. Methods: CSF biomarkers measured by the LUMIPULSE G600II platform and qualitative visualization of amyloid positron emission tomography (a-PET) were performed in all the patients. We established a cut-off for each single biomarker and Aß1-42/Aß1-40 ratio that optimized their agreement with a-PET using ROC curves. Sensitivity, Specificity, and Overall Percent of Agreement are assessed using a-PET or clinical diagnosis as gold standard for every cut-off. Also, we established a data-driven cut-off from our cognitively unimpaired cohort. We then analyzed changes in ATN classification. Results: One hundred and ten patients were recruited. Sixty-six (60%) were a-PET positive. PET-driven cut-offs were: pTau > 57, tTau > 362.62, Aß1-42/Aß1-40 < 0.069. For a single biomarker, pTau showed the highest accuracy (AUC 0.926). New PET-driven cut-offs classified patients similarly to manufacturer cut-offs (only two patients changed). However, 20 patients (18%) changed when data-driven cut-offs were used. Conclusions: We established our sample's best CSF biomarkers cut-offs using a-PET as the gold standard. These cut-offs categorize better symptomatic subjects than data-driven in ATN classification, but they are very similar to the manufacturer's.

Plasma Phosphorylated Tau 231 Increases at One-Year Intervals in Cognitively Unimpaired Subjects.

Background: Plasma biomarkers of Alzheimer's disease (AD) constitute a non-invasive tool for diagnosing and classifying subjects. They change even in preclinical stages, but it is necessary to understand their properties so they can be helpful in a clinical context. Objective: With this work we want to study the evolution of p-tau231 plasma levels in the preclinical stages of AD and its relationship with both cognitive and imaging parameters. Methods: We evaluated plasma phosphorylated (p)-tau231 levels in 146 cognitively unimpaired subjects in sequential visits. We performed a Linear Mixed-effects Model to analyze their rate of change. We also correlated their baseline levels with cognitive tests and structural and functional image values. ATN status was defined based on cerebrospinal fluid biomarkers. Results: Plasma p-tau231 showed a significant rate of change over time. It correlated negatively with memory tests only in amyloid-positive subjects. No significant correlations were found with any imaging measures. Conclusions: Increases in plasma p-tau231 can be detected at one-year intervals in cognitively healthy subjects. It could constitute a sensitive marker for detecting early signs of neuronal network impairment by amyloid.

Influence of Physiological Variables and Comorbidities on Plasma Aß40, Aß42, and p-tau181 Levels in Cognitively Unimpaired Individuals.

Plasma biomarkers for Alzheimer's disease (AD) are a promising tool that may help in early diagnosis. However, their levels may be influenced by physiological parameters and comorbidities that should be considered before they can be used at the population level. For this purpose, we assessed the influences of different comorbidities on AD plasma markers in 208 cognitively unimpaired subjects. We analyzed both plasma and cerebrospinal fluid levels of Aß40, Aß42, and p-tau181 using the fully automated Lumipulse platform. The relationships between the different plasma markers and physiological variables were studied using linear regression models. The mean differences in plasma markers according to comorbidity groups were also studied. The glomerular filtration rate showed an influence on plasma Aß40 and Aß42 levels but not on the Aß42/Aß40 ratio. The amyloid ratio was significantly lower in diabetic and hypertensive subjects, and the mean p-tau181 levels were higher in hypertensive subjects. The glomerular filtration rate may have an inverse relationship on plasma Aß40 and Aß42 levels but not on the amyloid ratio, suggesting that the latter is a more stable marker to use in the general population. Cardiovascular risk factors might have a long-term effect on the amyloid ratio and plasma levels of p-tau181.

Empathy as a crucial skill in disrupting disparities in global brain health.

Brain health refers to the state of a person's brain function across various domains, including cognitive, behavioral and motor functions. Healthy brains are associated with better individual health, increased creativity, and enhanced productivity. A person's brain health is intricately connected to personal, social and environmental factors. Racial, ethnic, and social disparities affect brain health and on the global scale these disparities within and between regions present a hurdle to brain health. To overcome global disparities, greater collaboration between practitioners and healthcare providers and the people they serve is essential. This requires cultural humility driven by empathy. Empathy is a core prosocial value, a cognitive-emotional skill that helps us understand ourselves and others. This position paper aims to provide an overview of the vital roles of empathy, cooperation, and interdisciplinary partnerships. By consciously integrating this understanding in practice, leaders can better position themselves to address the diverse challenges faced by communities, promote inclusivity in policies and practices, and further more equitable solutions to the problem of global brain health.