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Background: Patient‐centered care for persons with Parkinson's disease (PwPD) is associated with positive outcomes, but is lacking in current healthcare systems. Objective: In this qualitative study, we solicited advice from PwPD to medical professionals, family members/friends, and newly‐diagnosed PwPD. Methods: Through an online survey, 275 PwPD answered open‐ended questions asking for their advice. Responses were analyzed using content analysis. Interrater reliability was 94.5%. Results: Three qualitative themes were identified. First, participants advised enhancing care and communication, with healthcare professionals balancing clinical constraints with compassion, and family/friends balancing support with appreciating autonomy of PwPD. The second theme was empowering PwPD through increasing their knowledge of the disease and care options. The third reflected the importance of focusing on well‐being and connection. Conclusion: The results highlight several gaps in meeting the needs of PwPD in healthcare settings and personal relationships, underscoring the importance of integrating their perspectives in shaping approaches to care. [ABSTRACT FROM AUTHOR]

The fluxes of dissolved organic carbon (DOC) through tidal marsh‐influenced estuaries remain poorly quantified and have been identified as a missing component in carbon‐cycle models. The extreme variability inherent to these ecosystems of the land‐ocean interface challenge our ability to capture DOC‐concentration dynamics and to calculate accurate DOC fluxes. In situ discrete and continuous measurements provide high‐quality estimates of DOC concentration, but these strategies are constrained spatially and temporally and can be costly to operate. Here, field measurements and high‐spatial‐resolution remote sensing were used to train and validate a predictive model of DOC‐concentration distributions in the Plum Island Estuary (PIE), a mesotidal saltmarsh‐influenced estuary in Massachusetts. A large set of field measurements collected between 2017 and 2023 was used to develop and validate an empirical algorithm to retrieve DOC concentration with a ±15% uncertainty from Sentinel‐2 imagery. Implementation on 141 useable images produced a 6‐year time series (2017–2023) of DOC distributions along the thalweg. Analysis of the time series helped identify river discharge, tidal water level (WL), and a marsh enhanced vegetation index 2 as predictors of DOC distribution in the estuary, and facilitated the training and validation of a simple model estimating the distribution. This simple model was able to predict DOC along the PIE thalweg within ±16% of the in situ measurements. Implementation for three years (2020–2022) illustrated how this type of remote‐sensing‐informed models can be coupled with the outputs hydrodynamic models to calculate DOC fluxes in tidal marsh‐influenced estuaries and estimate DOC export to the coastal ocean. Plain Language Summary: The lateral transfer of DOC from tidal saltmarsh estuaries to the coastal ocean is not well represented in carbon‐cycle models. These estuaries are influenced by terrestrial processes, riverine and marsh inputs, and tidal fluctuations that combine to create complex dynamics of DOC concentration and complicate the quantification of DOC fluxes used to compute carbon budgets. Here, we used a combination of field measurements and high‐spatial‐resolution satellite imagery to develop and test a model predicting DOC concentrations along a tidal saltmarsh estuary in Massachusetts from three environmental variables (i.e., tidal WL, river discharge, and a satellite‐derived index of saltmarsh‐biomass). A test using an independent data set revealed this simple model can estimate DOC concentrations within ±16% of the values measured in the laboratory. A simulation conducted for a continuous period of 3 years (15‐min time step) showed that the model produced realistic DOC distributions and captured DOC dynamics adequately in the estuary. The model outputs can easily be coupled with hydrodynamic models to quantify the lateral transfer of DOC from tidal saltmarsh estuaries to the coastal ocean and inform carbon‐cycle models. Key Points: In situ data and satellite remote sensing used to develop and validate a predictive model of dissolved organic carbon (DOC) concentration in tidal saltmarsh estuaryDOC dynamics in tidal estuary were predicted accurately (within 16% of in situ DOC) from river discharge, water level, and marsh enhanced vegetation index 2Modeled DOC dynamics can be combined with hydrodynamic models to calculate DOC fluxes in tidal estuaries and inform carbon cycle models [ABSTRACT FROM AUTHOR]

Background: The largest identified kindred worldwide with a single mutation causing autosomal-dominant Alzheimer's disease (ADAD) is a family from Antioquia, Colombia, carrying the Presenilin-1 (PSEN1) E280A (Paisa) mutation. The majority of mutation carriers develop dementia, typically commencing in their late 30 s, with a median onset age of 49 years. Cognitive decline is a hallmark feature. Objective: This review synthesizes the existing literature on neuropsychological assessments in PSEN1 E280A mutation carriers throughout their lifespan. We provide a comprehensive overview of cognitive outcomes in this unique population. Methods: We reviewed and integrated the published research, analyzing studies on neuropsychological assessments in PSEN1 E280A carriers. Our focus was on measures of verbal, semantic, episodic, and spatial memory, and encompassed other cognitive domains such as language, attention, visuospatial memory, and executive functioning. Results: Verbal, semantic, episodic, and spatial memory emerged as the most sensitive indicators of preclinical changes in PSEN1 E280A carriers. Inconsistencies were noted in findings from tests assessing language, attention, visuospatial memory, and executive functioning, suggesting potential limitations in detecting early cognitive changes in PSEN1 mutation carriers. Specific cognitive tasks developed for this population proved effective but underutilized. Conclusions: The review underscores the importance of continued test development tailored to detect early cognitive changes in PSEN1 E280A carriers, potentially enhancing ADAD screening. Furthermore, investigating ADAD mutations in children may identify early changes in AD and enhance our understanding of neuropsychological functioning across the lifespan. This synthesis provides valuable insights for researchers, clinicians, and policymakers engaged in the study and management of ADAD. [ABSTRACT FROM AUTHOR]

Accumulating world knowledge is a major task of development and education. The productive process of self-derivation through memory integration seemingly is a valid model of the process. To test the model, we examined relations between generation and retention of new factual knowledge via self-derivation through integration and world knowledge as measured by standardised assessments. We also tested whether the productive process of self-derivation predicted world knowledge even when a measure of learning through direct instruction also was considered. Participants were 162 children ages 8–12 years (53% female; 15% Black, 6% Asian, 1% Arab, 66% White, 5% mixed race, 7% unreported; 1% Latinx). Age accounted for a maximum of 4% of variance in self-derivation and retention. In contrast, substantial individual variability related to general knowledge and content knowledge in several domains, explaining 20–40% variance. In each domain for which self-derivation performance was a unique predictor, it explained a nominally greater share of the variance than the measure of learning through direct instruction. The findings imply that individual variability in self-derivation has functional consequences for accumulation of semantic knowledge across the elementary-school years. [ABSTRACT FROM AUTHOR]

Background: Self‐report of motor and non‐motor symptoms is integral to understanding daily challenges of persons with Parkinson's disease (PwPD). Care partners are often asked to serve as informants regarding symptom severity, raising the question of concordance with PwPD self‐reports, especially regarding internalized (not outwardly visible) symptoms. Objectives: Concordance between PwPD and informant ratings of motor and non‐motor symptoms was evaluated across multiple domains. Methods: In 60 PwPD‐informant pairs, we compared ratings on 11 online self‐report measures comprising 33 total scores, 2/3 of which represented purely internalized symptoms. For discordant scores, multiple regression analyses were used to examine demographic/clinical predictors. Results: Though concordant on 85% of measures, PwPD endorsed more non‐motor symptoms, bodily discomfort, stigma, and motor symptoms than informants. For PwPD, younger age, greater disease severity, and female gender predicted discordance. Conclusions: Discordance between PwPD and informants on measures assessing symptoms that cannot be outwardly observed may require targeted education. [ABSTRACT FROM AUTHOR]

Objective Identifying persons needing mental health services is hampered by stigma-related underreporting of symptoms, especially by men. Men with Parkinson's disease (PD) consistently report lower rates of depression than women in in-person studies. We predicted that online anonymity would elicit more gender-based parity in depression endorsement. Method We administered the Beck Depression Inventory-II (BDI-II) online to 344 participants with PD (52% women). Depression was defined as BDI-II score >13 and/or use of antidepressant medications. Results Overall depression prevalence was consistent with in-person studies, but with no significant difference between men and women. Conclusions Online methods may circumvent barriers to depression identification in men with PD. [ABSTRACT FROM AUTHOR]

Objectives: Alzheimer's disease (AD) is known to impact semantic access, which is frequently evaluated using the Category Fluency (Animals) test. Recent studies have suggested that in addition to overall category fluency scores (total number of words produced over time), poor clustering could signal AD-related cognitive difficulties. In this study, we examined the association between category fluency clustering performance (i.e., stating words sequentially that are all contained within a subcategory, such as domestic animals) and brain pathology in individuals with autosomal dominant Alzheimer's disease (ADAD). Methods: A total of 29 non-demented carriers of the Presenilin1 E280A ADAD mutation and 32 noncarrier family members completed the category fluency test (Animals) and the Mini-Mental State Examination (MMSE). The participants also underwent positron emission tomography (PET) scans to evaluate in vivo amyloid-beta in the neocortex and tau in medial temporal lobe regions. Differences between carriers and noncarriers on cognitive tests were assessed with Mann-Whitney tests; associations between cognitive test performance and brain pathology were assessed with Spearman correlations. Results: Animal fluency scores did not differ between carriers and noncarriers. Carriers, however, showed a stronger association between animal fluency clustering and in vivo AD brain pathology (neocortical amyloid and entorhinal tau) relative to noncarriers. Conclusion: This study indicates that using category fluency clustering, but not total score, is related to AD pathophysiology in the preclinical and early stages of the disease. [ABSTRACT FROM AUTHOR]

Introduction: Obstructive sleep apnea (OSA) is associated with subjective cognitive decline (SCD) and increased risk of cognitive decline and dementia. These relations are understudied in ethnoracially diverse groups. We examined associations among self-reported OSA risk, SCD, and cognitive performance in community-dwelling older Latinos. High OSA risk was hypothesized to be associated with greater SCD and worse cognitive performance., Methods: 112 participants (40 female) from the Boston Latino Aging Study (BLAST) were included (Mage=67.0 years [SD=8.0]; Meducation=11.0 years [SD=5.1]). Participants completed the Preclinical Alzheimer's Cognitive Composite-5 (PACC5; z-scores), the Berlin Questionnaire (high vs. low OSA risk), and the Cognitive Function Instrument (SCD). The Mini-Mental State Examination (MMSE) indexed global cognition. Hierarchical regressions assessed associations among OSA risk, SCD, and cognitive performance while controlling for demographics. T-tests examined demographic and cognitive differences between those at high/low OSA risk., Results: On average, participants had an MMSE score of 25.9 (SD=3.7, range 11-30; 37 participants with MMSE<26) and mild SCD (CFI; M=4.2 [3.6]). OSA risk did not predict SCD (β=.09, p=.33) or PACC5 performance (β=.01, p=.92). No differences in SCD or PACC5 performance were observed between those at low vs. high OSA risk (p's≥.21)., Conclusion: Preliminary findings suggest that self-reported OSA risk may not signal cognitive decline risk for older Latinos. Questionnaires screening for OSA may need to be used in tandem with other assessments to identify those experiencing early cognitive decline. More work with larger sample sizes is needed; BLAST data collection is ongoing., (S. Karger AG, Basel.)

Functional Near-Infrared Spectroscopy (fNIRS) holds transformative potential for research and clinical applications in neuroscience due to its non-invasive nature and adaptability to real-world settings. However, despite its promise, fNIRS signal quality is sensitive to individual differences in biophysical factors such as hair and skin characteristics, which can significantly impact the absorption and scattering of near-infrared light. If not properly addressed, these factors risk biasing fNIRS research by disproportionately affecting signal quality across diverse populations. Our results quantify the impact of various hair properties, skin pigmentation as well as head size, sex and age on signal quality, providing quantitative guidance for future hardware advances and methodological standards to help overcome these critical barriers to inclusivity in fNIRS studies. We provide actionable guidelines for fNIRS researchers, including a suggested metadata table and recommendations for cap and optode configurations, hair management techniques, and strategies to optimize data collection across varied participants. This research paves the way for the development of more inclusive fNIRS technologies, fostering broader applicability and improved interpretability of neuroimaging data in diverse populations.