Central Coordination Research Articles

The effect of study partner characteristics on the reporting of neuropsychiatric symptoms across the neurocognitive spectrum.

We explored the influence of study partner (SP) characteristics on SP-reported neuropsychiatric symptoms (NPS) presence across the neurocognitive spectrum and on the prognostic utility of mild behavioral impairment (MBI). We performed cross-sectional (n = 26,748) and longitudinal (n = 12,794) analyses using participant-SP dyad data from the National Alzheimer's Coordinating Center. Participants were cognitively normal (CN; n = 11,951) or had mild cognitive impairment (MCI; n = 5686) or dementia (n = 9111). SPs rated NPS using the Neuropsychiatric Inventory Questionnaire. We used multivariable logistic regression to model the association between SP characteristics (age, sex, and relationship to participant [spouse, child, and other]) and NPS status (outcome). Cox regressions assessed SP characteristics as moderators of MBI associations with incident dementia or as predictors of incident dementia in MBI + participants only. Among CN persons, younger, female, and spouse SPs reported NPS more frequently. In MCI, younger SPs and those who were spouses or children of participants reported higher NPS odds. For dementia participants, NPS odds were higher in female and spouse SPs. MBI associations with incident dementia were slightly weaker when SPs were older but did not depend on SP sex or relationship to participant. Among MBI + participants with spouse or child SPs, hazard for dementia was higher when compared to MBI + participants with other SPs. SP age, sex, and relationship to participant influence NPS reporting across the neurocognitive spectrum, with potential implications for MBI prognosis. Considering SP characteristics may enhance the accuracy of NPS assessments, which may facilitate therapy planning and prognosis.

Association of education attainment, smoking status, and alcohol use disorder with dementia risk in older adults: a longitudinal observational study

BackgroundPrevious research on the risk of dementia associated with education attainment, smoking status, and alcohol use disorder (AUD) has yielded inconsistent results, indicating potential heterogeneous treatment effects (HTEs) of these factors on dementia risk. Thus, this study aimed to identify the important variables that may contribute to HTEs of these factors in older adults.MethodsUsing 2005–2021 data from the National Alzheimer’s Coordinating Center (NACC), we included older adults (≥ 65 years) with normal cognition at the first visit. The exposure of interest included college education or above, current smoking, and AUD and the outcome was all-cause dementia. We applied doubly robust learning to estimate risk differences (RD) and 95% confidence intervals (CI) between exposed and unexposed groups in the overall cohort and subgroups identified through a decision tree model.ResultsOf 10,062 participants included, 929 developed all-cause dementia over a median 4.4-year follow-up. College education or above was associated with a lower risk of all-cause dementia in the overall population (RD, -1.5%; 95%CI, -2.8 to -0.3), especially among the subpopulations without hypertension, regardless of the APOE4 status. Current smoking was not related to increased dementia risk overall (2.8%; -1.5 to 7.2) but was significantly associated with increased dementia risk among men with (21.1%, 3.1 to 39.1) and without (8.4%, 0.9 to 15.8) cerebrovascular disease. AUD was not related to increased dementia risk overall (2.0%; -7.7 to 11.7) but was significantly associated with increased dementia risk among men with neuropsychiatric disorders (31.5%; 7.4 to 55.7).ConclusionsOur studies identified important factors contributing to HTEs of education, smoking, and AUD on risk of all-cause dementia, suggesting an individualized approach is needed to address dementia disparities.

Coping patterns associations with cognitive function in older adults.

Cognitive function may contribute to variability in older adults' ability to cope with chronic stress; however, limited research has evaluated this relationship. This study investigated the relationship between theoretically derived coping domains and cognitive function in 165 middle-to-older adults during the Omicron stage of COVID-19. Participants completed a clinical interview and self-report measures of health. The National Alzheimer's Coordinating Center Uniform Data Set neuropsychological battery was used to evaluate memory, language, executive function/speed, and working memory. Structural equation modeling evaluated the underlying factor structure of the Brief COPE adapted for COVID-19. The data supported the proposed second-order Approach factor comprised of Problem-Solving and Emotion Regulation (ER) strategies and a first-order Avoidance factor. Higher Avoidance was associated with greater depression symptoms, lower income and worse memory, executive function, working memory, and verbal fluency performance. Higher Problem-Solving was associated with better verbal fluency performance. ER strategies were not significantly associated with cognitive function. The use of Problem-Solving was not associated with less Avoidance. Greater use of Problem-Solving, ER, and Avoidance were all associated with higher levels of stress. Post-hoc analyses found that higher Acceptance was the only coping strategy associated with less stress. These findings demonstrate that older adults with worse cognitive function were more likely to use Avoidance during the pandemic, which could result in prolonged stress and adverse health consequences. Future research is warranted to investigate whether acceptance-based interventions reduce the avoidance and impact of stress on health in vulnerable older adults.

Comparison of Explainable AI Models for MRI-based Alzheimer's Disease Classification.

Deep learning models based on convolutional neural networks (CNNs) have been used to classify Alzheimer's disease or infer dementia severity from 3D T1-weighted brain MRI scans. Here, we examine the value of adding occlusion sensitivity analysis (OSA) and gradient-weighted class activation mapping (Grad-CAM) to these models to make the results more interpretable. Much research in this area focuses on specific datasets such as the Alzheimer's Disease Neuroimaging Initiative (ADNI) or National Alzheimer's Coordinating Center (NACC), which assess people of North American, predominantly European ancestry, so we examine how well models trained on these data generalize to a new population dataset from India (NIMHANS cohort). We also evaluate the benefit of using a combined dataset to train the CNN models. Our experiments show feature localization consistent with knowledge of AD from other methods. OSA and Grad-CAM resolve features at different scales to help interpret diagnostic inferences made by CNNs.

Scaling up! Staff e-learning for a national take-home naloxone program.

A staff e-learning course was developed to prepare for scaling up a national take-home naloxone (THN) program in Norway. The aims of the study were to (a) describe participant characteristics for those that completed a THN e-learning course, (b) compare opioid overdose knowledge scores before and after e-learning course completion, and (c) to explore subsequent THN distribution by those trained. This was a quasi-experimental pre-test, post-test longitudinal cohort study of individuals completing a THN e-learning course from April 2021 to May 2022. Frequency analyses were performed for participant characteristics and subsequent naloxone distributions at 1-week and 1-month follow-up. The opioid overdose knowledge scale (OOKS) was used to measure pre-test-post-test knowledge among participants. Wilcoxon signed-rank test was performed for comparison between pre-test and post-test. Effect size was calculated using Cohen criteria. In total, 371 individuals were included in this study. Most were either nurses or social workers (n = 277, 75%). Participant knowledge increased by medium or large effect for all items measured. At 1-month follow-up, 15% reported naloxone distribution. During the study period, 94 naloxone kits were distributed. Major reasons for not distributing were "clients not interested", "workplace not distributing" and "workplace in process of distributing". Our findings suggest that an e-learning course is equally effective in terms of knowledge transfer as an in-person classroom setting, and may provide engagement in terms of naloxone distribution. However, our findings also emphasize the importance of clear implementation routines, including support from central coordinators to optimize the implementation process.

A - 111 Neuropsychological Functioning in those with Chronic Traumatic Encephalopathy

Abstract Objective To differentiate neurocognitive performance between those with chronic traumatic encephalopathy neuropathologic change (CTE-NC) and matched CTE-negative individuals. Methods Data were obtained from the National Alzheimer’s Coordinating Center (NACC). Participants with mild cognitive impairment (MCI) or dementia and CTE-NC (n = 22) were matched approximately 1:3 to those with MCI/dementia but without CTE-NC (n = 64) on demographics (age of initial cognitive diagnosis, education, sex) and postmortem Alzheimer’s and Lewy body neuropathology. ANCOVAs (covarying for symptom duration and cognitive diagnosis) compared neurocognitive measures between groups (MMSE and neuropsychological battery composites of Attention, Executive Function, and Speed [AEFS], Memory, and Language). Results Participants were all male, 89.3% White, and averaged 16.3 years of education. They were, on average, 74.8 years of age (SD = 7.3) when diagnosed with MCI/dementia and had 4.2 years (SD = 4.2) of cognitive symptoms prior to MCI/dementia diagnosis. Rates of comorbid moderate/severe Alzheimer’s or Lewy body pathology were high (n = 13, 54%) in the CTE-NC group. At time of cognitive diagnosis, individuals with CTE-NC performed slightly better on the MMSE (F = 4.510, p = 0.037, CTE-NC+ M = 26.03 [1.05] vs. CTE-NC- M = 23.44 [0.58]). No differences in AEFS [F = 0.280, p = 0.599], Memory [F = 2.265, p = 0.137], or Language [F = 3.424, p = 0.069] were observed between groups. Conclusions Those with CTE-NC did not greatly differ in neuropsychological domains, but had relatively higher MMSE scores compared to those without CTE-NC. This is the largest clinicopathological investigation utilizing in-vivo neurocognitive data, though NACC lacks CTE-NC severity/distribution data for sensitivity analyses. Nonetheless, results have implications for CTE clinical criteria frameworks and larger clinicopathological studies are needed to determine if CTE-NC has distinct neurocognitive features.

A - 131 Patterns of Functional Decline in Alzheimer Biomarker-Positive Vs. Negative Cognitive Impairment

Abstract Objective To contrast longitudinal patterns of functional decline between groups of cognitively impaired individuals with or without biomarker support for Alzheimer’s disease (ad). Method We requested data from the National Alzheimer’s Coordinating Center on individuals who underwent serial evaluation with the Functional Activities Questionnaire (FAQ) and those for whom cerebrospinal fluid biomarkers for ad were available. By cross-referencing the two datasets, we identified 570 subjects, 71 of whom were biomarker positive and 499 biomarker negative. Item-level FAQ item-level scores were then entered as predictor variables into lagged mixed-effects regression models with a single FAQ item as the dependent variable in each model (one model for each of the ten FAQ items). Coefficients for statistically significant predictors of follow-up FAQ items were plotted as arcs on a directed graph, with one vertex for each of the ten FAQ items. We repeated this process for biomarker positive and negative individuals and created a map depicting effect size differences, i.e., biomarker positive minus biomarker-negative regression coefficients (Δ = β + − β-) for statistically significant arcs (α = 0.05). Results Twelve out of 21 arcs that were significant in the biomarker-positive individuals were significant only for this group. The largest effect size difference was STOVE → STOVE (Δ = 0.233). Twenty of 29 arcs that were significant in the biomarker-negative individuals were significant only for this group. The largest effect size difference was GAMES → GAMES (Δ = −0.168). Conclusion ad biomarker status modulated the patterns of longitudinal functional change in this sample.

A - 114 Exploring Alzheimer’s Disease: the Interplay of Depression, Substance Use, and Neurocognition

Abstract Objective Depression and substance use (SU) can significantly impact one’s neurocognition and are potential risk factors for Alzheimer’s Disease (ad). The project aimed to explore whether a history of depression and/or SU could predict baseline performance on neuropsychological assessment among individuals with and without ad. Method Data from the National Alzheimer’s Coordinating Center (NACC) was analyzed. N = 9114 participants (41.5% Male, 58.5% Female; 56.7% Normal Cognition, 43.2% ad) at their first visit were selected. A series of linear regression models, separated by presence of ad diagnosis, were run to determine if a history of depression, and/or SU, age, race, sex, education level, and APOE status would predict performance on selected neuropsychological assessments measuring facets of executive functioning (EF) (Trail Making, Digit Span, and Wechsler Adult Intelligence Scale (WAIS)). Results Depression was a significant predictor of performance on the WAIS in the normal cognition (β = −0.12,p < 0.001) and ad (β = −0.14,p < 0.001) groups, on Number of Correct Digit Span Backward Trials in the normal cognition (β = 0.09,p < 0.01) and ad (β = −0.10,p < 0.01) groups, and on Number of Correct Digit Span Forward Trials in the ad group (β = −0.11,p < 0.001). SU was a significant predictor of performance on Number of Correct Digit Span Backward Trials in the ad group (β = 0.20,p < 0.01). Demographic variables were also significant. Conclusions Depression predicted performance on multiple neuropsychological assessments across diagnostic groups compared to SU. EF facets measured across assessments may have been further impacted by ad and mental health history compared to those with normal cognition endorsing mental health history.

A - 128 Informant Characteristics Impact Clinical Dementia Rating Scale Sum of Boxes in Mild Cognitive Impairment

Abstract Objective The Clinical Dementia Rating (CDR) Scale is an informant-based instrument widely used in clinical and research settings to stage dementia severity. Informant-based reports of functioning have been shown to be influenced by informant characteristics, indicating a potential source of bias. The current study adds to this growing area of research by exploring the differential impact of informant characteristics on CDR Sum of Boxes (CDR-SB) among non-Hispanic White (NHW), non-Hispanic Black (NHB) and Hispanic older adults with mild cognitive impairment (MCI). Method Participants included 2775 older adults diagnosed with MCI from the National Alzheimer’s Coordinating Center Uniform Data Set. Multiple linear regression models with forward selection evaluated the extent to which various informant characteristics predicted CDR-SB scores in the whole sample and NHW (n = 2170), NHB (n = 495), and Hispanic (n = 110) groups, covarying for participant demographics and cognition (MoCA). Results Informant sex, education, age, relationship type, and cohabitation status significantly predicted CDR-SB scores in this sample (R2 = 0.096, p < 0.001). Models stratified by race and ethnicity accounted for 20.2%, 10.3%, and 6.9% of the variance in CDR-SB scores in Hispanic, NHB, and NHW groups, respectively (ps < 0.001). Variability in model predictors was observed across groups, with informant characteristics accounting for more model variance than participant demographics in Hispanic and NHB groups. Results remained significant after adjusting for multiple comparisons. Conclusions Informant characteristics and relational factors may influence perceptions of participant functioning on the CDR-SB and may particularly affect scores among Hispanic older adults with MCI, though further validation in community-based cohorts with adequate racial and ethnic representation is warranted.

The Association of Cerebrospinal Fluid Biomarkers of Alzheimer’s Disease with Cognitive Intra-Individual Variability

Abstract Objective Cognitive intra-individual variability (IIV) is a sensitive predictor of cognitive decline and disease severity in Alzheimer’s disease (AD). Despite its sensitivity, whether IIV is merely a psychometric artifact or disease pathology biomarker remains unknown. The present study evaluated the association between IIV and cerebrospinal fluid (CSF) biomarkers of AD. Method Participants included 422 individuals from the National Alzheimer’s Coordinating Center Unified Dataset 3.0 who completed baseline neuropsychological assessment and had CSF data. All participants were adult monolingual English speakers. Participants with vision or hearing impairments were excluded. Cases were stratified into cognitively normal (n = 267) and AD groups (n = 155; mild cognitive impairment = 50, dementia = 105). Cross-sectional IIV was calculated by obtaining the individual standard deviation (iSD) of ten cognitive tests. Finally, the coefficient of variation (CoV) was computed by dividing iSD by the participant’s overall test battery mean. Non-parametric Spearman-rank correlations were used to assess the relation between CoV and CSF biomarkers, including beta-amyloid 1–42, total tau (t-tau), and phosphorylated tau (p-tau181). Results In the AD group, CoV was positively correlated with p-tau181 (r = 0.285, p = 0.003) and t-tau (r = 0.241, p = 0.009), and negatively correlated with beta-amyloid 1–42 (r = −0.314, p < 0.001). Correlations between CoV and CSF biomarkers were not significant in the cognitively normal group for beta-amyloid 1–42 (r = 0.076, p = 0.215), p-tau181 (r = −0.014, p = 0.840), and t-tau (r = −0.046, p = 0.485). Conclusions In people with mild cognitive impairment and dementia of presumed AD etiology, cognitive IIV is associated with CSF biomarkers. These findings provide preliminary evidence that IIV is not merely a statistical artifact, but is associated with AD neuropathology.

Advancements in Pan-Canadian Data Access and Analysis Facilitation: Insights from Collaborative Health Research supported in Alberta, British Columbia, and Ontario

ObjectiveTo highlight progress in facilitating and supporting pan-Canadian data analysis research that is supported by a central coordinating center. This process will be illustrated with the use of a recently completed project that has been supported using data from Alberta, British Columbia, and Ontario. ApproachThe project represents a significant endeavor within the central coordinating center, as it necessitates coordination for data access, data importation and analytical support across three provinces. The focus will be on the administrative processes refined to support collaborative research endeavors. While specific project details will remain undisclosed, procedural enhancements within the central coordinating center framework will be highlighted. Key discussion points include standardized protocols for data access, collaborative efforts to streamline data importation, and facilitation of analytical support across jurisdictions. The type of cross-jurisdictional analytic support will as well be highlighted; data variables harmonization and sharing of data algorithms cohorts across the participating provincial data centers in support of the meta-analysis. ResultsThe successful completion of the final data analysis underscores the effectiveness of a unified data access coordination center for researchers seeking multi-regional health data in Canada. By highlighting advancements enabled by the central coordinating center and provincial data centers, this submission aims to inform researchers about the current landscape of pan-Canadian research and foster opportunities for future collaboration. ImplicationsSharing insights and lessons from this project emphasizes the advancements facilitated by the central coordinating center and provincial data centers, informing researchers about the potential of pan-Canadian research, and encouraging future collaborative endeavors.

Interfacility Patient Transfers During COVID-19 Pandemic: Mixed-Methods Study.

The United States lacks a national interfacility patient transfer coordination system. During the coronavirus 2019 (COVID-19) pandemic, many hospitals were overwhelmed and faced difficulties transferring sick patients, leading some states and cities to form transfer centers intended to assist sending facilities. In this study we aimed to explore clinician experiences with newly implemented transfer coordination centers. This mixed-methods study used a brief national survey along with in-depth interviews. The American College of Emergency Physicians Emergency Medicine Practice Research Network (EMPRN) administered the national survey in March 2021. From September-December 2021, semi-structured qualitative interviews were conducted with administrators and rural emergency clinicians in Arizona and New Mexico, two states that started transfer centers during COVID-19. Among 141 respondents (of 765, 18.4% response rate) to the national EMPRN survey, only 30% reported implementation or expansion of a transfer coordination center during COVID-19. Those with new transfer centers reported no change in difficulty of patient transfers during COVID-19 while those without had increased difficulty. The 17 qualitative interviews expanded upon this, revealing four major themes: 1)limited resources for facilitating transfers even before COVID-19; 2)increased number of and distance to transfer partners during the COVID-19 pandemic; 3)generally positive impacts of transfer centers on workflow, and 4)the potential for continued use of centers to facilitate transfers. Transfer centers may have offset pandemic-related transfer challenges brought on by the COVID-19 pandemic. Clinicians who frequently need to transfer patients may particularly benefit from ongoing access to such transfer coordination services.

Synthesis and characterization of catalytically active Ni(II) complexes with Bis(phenol)diamine ligands

A novel N,N’-dimethylethylenediamine derivative of substituted bis(phenol)diamine ligands, namely 2-(tert-butyl)-4-methylphenol in H2L1, was synthesized by a convenient green procedure. Nickel)II) complex [NiL1] 1 has been synthesized and characterized by various methods along with crystal structure determined. Ni(II) coordination center in a mononuclear complex is surrounded by two phenolate oxygen atoms and two amine nitrogen atoms of the ligand in a square planar arrangement. The magnetic susceptibility of the title complex indicates a paramagnetic behavior above 150 K, while strong ferromagnetism below 100 K. Furthermore, the cyclic voltammetry studies show two ligand-centered oxidation of the phenolate groups to phenoxyl radical and the metal-centered reduction of Ni(II) to Ni(0). The Glaser coupling reaction of phenylacetylene was also studied. A strong catalytic activity at room T in THF solvent is observed for 1 in the presence of zinc powder as a reducing agent. A full conversion rate was achieved after 7 h at 25 °C. The DFT analysis corroborates with the square-planar NiO2N2 chromophore of 1 being reduced in catalytically active Ni(0) by applied Zn. The calculated Gibbs free energy of the reaction leading to the formation of the substrate Ni-complex is favorable endothermic. Most of the data for 1 were obtained also for the very similar previously reported [NiL2] 2, with 2,4- di tert-butylphenol in H2L2, which were than compared.

Designing a Website to Support a Multisite, International Clinical Trial.

Safe and reliable implementation of complex study protocols in multisite clinical trials requires that all study personnel have 24/7 access to up-to-date study materials. Study websites can serve as an electronic manual of operations (eMOO) to support trial conduct. We describe the development, organization, and maintenance of a study website and eMOO to facilitate quick and efficient communication during conduct of a complex, multisite, international clinical trial. We worked closely with our information technology (IT) department to develop and maintain our study website, which includes a public home page, a section for parents and families, and three password-protected portals that serve as an eMOO for (a) study sites, (b) study site investigators, and (c) the operations team (e.g., clinical coordination center, data coordination center). The public home page is helpful for families contemplating study participation and for nonparticipating sites considering joining our trial. The patient and family education section supports family participation in the study. The study site portal contains all information needed for local study teams to safely manage a study patient. The investigator portal provides access to research-specific materials needed to lead the study at each site. The operations team portal supports overall study management. For other scientists considering use of a study website for their multisite research, we recommend close collaboration with IT for development and maintenance, limited and clearly defined roles for version control, and use of unmodifiable file formats to prevent unapproved alterations of study materials. While investment in development and maintenance has been significant, we have appreciated marked value to our operations team and study sites. Our study website development process is relevant to other scientists conducting multisite clinical research.

The association between cigarette smoking and dementia with Lewy bodies

IntroductionCigarette smoking is associated with a reduced risk of Parkinson's disease (PD). As dementia with Lewy bodies (DLB) and PD share core neuropathologic features, we set out to examine the relationship between smoking and DLB. MethodsDiagnosis at baseline visit and smoking history of participants ≥50 years old in the National Alzheimer's Coordinating Center (NACC) cohort were evaluated in this cross-sectional study. Odds of diagnosis of cognitive impairment due to DLB, PD, vascular dementia (VD), or Alzheimer's disease (AD) compared to normal cognition based on smoking status and duration were determined using logistic regression. Results37,478 participants were included (mean age 72 years (SD 9), 57 % female). The odds of DLB were reduced in all smoking status groups compared to never smokers (OR (95 % CI)): ever smokers 0.850 (0.745–0.971), former smokers 0.871 (0.761–0.997), current smokers 0.640 (0.419–0.947)) and in all smoking duration groups. As expected, the odds of PD were reduced in all smoking groups and fell with longer smoking duration. The odds of VD were increased in the current smoking group and rose with greater smoking duration. The odds of AD were unchanged in current smokers, decreased in ever and former smokers, and increased with longer cumulative smoking duration. ConclusionsCigarette smoking is associated with lower odds of diagnosis of DLB at baseline visit in the NACC cohort. In the context of the well-established reduced risk of PD among smokers, this preliminary evidence of a potential protective effect of smoking on DLB warrants further study.

Research on positioning accuracy of the swivel head of milling and turning complex machining center

Abstract This article focuses on the swivel head of a milling-turning complex machining center and establishes a geometric error model between the rotary axes based on the multi-body system theory and the homogeneous coordinate transformation method. The double ball bar (DBB) is used to identify the geometric errors of the machine tool swivel head position-independent by measuring circular trajectories. The impact of PIGEs on the measurement trajectory is simulated. The swivel head is rotated at four angles (B0°, B45°, B90°, B-15°), and the laser tracker is used to analyze and study the linear axis straightness, perpendicularity, and the center coordinates and plane errors of the swivel head movement along the XZ plane. A swivel head rotation accuracy test fixture is designed to correct the positioning accuracy of a swivel head with a 45° inclination of the rotation axis. The research results show that the fluctuation of the center plane degree of freedom of the swivel head moving along the XZ plane is small, and the maximum value is 0.0086mm. Under the 45° angle posture of the swivel head, both the center coordinate error value and the plane error value are the largest. The simulation results of the swivel head position error are fairly consistent with the center coordinate error of the swivel head plane movement. A backward tilt displacement of 0.01mm~0.015mm of the machine column during assembly can reduce the influence of the weight of the swivel head on the perpendicularity and straightness of the vertical reciprocating motion, and adding auxiliary support near the base of the swivel head zero position can reduce machine straightness error.

Neuropsychiatric symptoms: Risk factor or disease marker? A study of structural imaging biomarkers of Alzheimer's disease and incident cognitive decline.

Neuropsychiatric symptoms (NPS) are risk factors for Alzheimer's disease (AD) but can also manifest secondary to AD pathology. Mild behavioral impairment (MBI) refers to later-life emergent and persistent NPS that may mark early-stage AD. To distinguish MBI from NPS that are transient or which represent psychiatric conditions (non-MBI NPS), we investigated the effect of applying MBI criteria on NPS associations with AD structural imaging biomarkers and incident cognitive decline. Data for participants (n = 1273) with normal cognition (NC) or mild cognitive impairment (MCI) in the National Alzheimer's Coordinating Center Uniform Data Set were analyzed. NPS status (MBI, non-MBI NPS) was derived from the Neuropsychiatric Inventory Questionnaire and psychiatric history. Normalized measures of bilateral hippocampal (HPC) and entorhinal cortex (EC) volume, and AD meta-region of interest (ROI) mean cortical thickness were acquired from T1-weighted magnetic resonance imaging scans. Multivariable linear and Cox regressions examined NPS associations with imaging biomarkers and incident cognitive decline, respectively. MBI was associated with lower volume and cortical thickness in all ROIs in both NC and MCI, except for EC volume in NC. Non-MBI NPS were only associated with lower HPC volume in NC. Although both of the NPS groups showed higher hazards for MCI/dementia than No NPS, MBI participants showed more rapid decline. Although both types of NPS were linked to HPC atrophy, only NPS that emerged and persisted in later-life, consistent with MBI criteria, were related to AD neurodegenerative patterns beyond the HPC. Moreover, MBI predicted faster progression to dementia than non-MBI NPS.

Lessons on the use of real-world data in medical device research: findings from the National Evaluation System for Health Technology Test-Cases.

Aim: Although the US FDA encourages manufacturers of medical devices to submit real-world evidence (RWE) to support regulatory decisions, the ability of real-world data (RWD) to generate evidence suitable for decision making remains unclear. The 2017 Medical Device User Fee Amendments (MDUFA IV), authorized the National Evaluation System for health Technology Coordinating Center (NESTcc) to conduct pilot projects, or 'Test-Cases', to assess whether current RWD captures the information needed to answer research questions proposed by industry stakeholders. We synthesized key lessons about the challenges conducting research with RWD and the strategies used by research teams to enhance their ability to generate evidence from RWD based on 18 Test-Cases conducted between 2020 and 2022. Materials & methods: We reviewed study protocols and reports from each Test-Case team and conducted 49 semi-structured interviews with representatives of participating organizations. Interview transcripts were coded and thematically analyzed. Results: Challenges that stakeholders encountered in working with RWD included the lack of unique device identifiers, capturing key data elements and their appropriate meaning in structured data, limited reliability of diagnosis and procedure codes in structured data, extracting information from unstructured electronic health record (EHR) data, limited capture of long-term study end points, missing data and data sharing. Successful strategies included using manufacturer and supply chain data, leveraging clinical registries and registry reporting processes to collect and aggregate data, querying standardized EHR data, implementing natural language processing algorithms and using multidisciplinary research teams. Conclusion: The Test-Cases identified numerous challenges working with RWD but also opportunities to address these challenges and improve researchers' ability to use RWD to generate evidence on medical devices.

Membrane transport of rare earth metal ions N, N’-bisdioctylphosphorylmethyl-1,4-diaminobutane by the active transport mechanism

The method of membrane extraction for rare earth elements (REE) using the carrier N, N’-bisdioctylphosphorylmethyl-1,4-diaminobutane (DPDA-8) ions, leveraging an active transport mechanism, has been optimized. The distribution of DPDA-8 within the membrane pores was confirmed using scanning electron microscopy (SEM). Both light and heavy REE extractions from a simulated solution using DPDA-8 and trioctylphosphine oxide (TOPO) in 1,2-dichlorobenzene were explored. The influence of feed solution pH, carrier and anion concentration, supported liquid membrane (SLM) type and stability, and cell temperature, among other parameters, were meticulously examined. The results indicate a decrease in permeability with a decrease in feed solution pH attributed to competitive acid transport through the membrane. Additionally, the formation of H-complexes between carriers and perchloric or phosphoric acids was investigated using Fourier Transform Infrared (FTIR) spectroscopy and X-ray diffraction (XRD) techniques. Changes in the stretching bands of amino and phosphine oxide groups in DPDA-8 were monitored and characterized. XRD analysis of the crystal structures of salts DPDA-6·ClO4 and DPDA-12·H2PO4 revealed a two-dimensional layered supramolecular organization with varying anion positions relative to hydrophobic fragments. The DPDA-8 carrier demonstrated significantly higher permeability values compared to TOPO, with differences in permeability exceeding twofold for certain metals. FTIR spectroscopy identified the main coordination centers of DPDA-8 during the liquid–liquid extraction of specific REEs.

Quantifying wildland fire resources deployed during the compound threat of COVID-19

Fire agencies across the United States must make complex resource allocation decisions to manage wildfires using a national network of shared firefighting resources. Firefighters play a critical role in suppressing fires and protecting vulnerable communities. However, they are exposed to health and safety risks associated with fire, smoke inhalation, and infectious disease transmission. The COVID-19 pandemic further complicated these risks, prompting fire agencies to propose resource management adaptations to minimize COVID-19 exposure and transmission. It is unclear if and how the pandemic may have operationally influenced wildland firefighting personnel resource use given compounding wildfire and COVID-19 risks. Therefore, we developed generalized linear mixed models that were fit using multiple integrated datasets to detect changes in personnel resource use for years prior to and during the COVID-19 pandemic, while controlling for historical fire and landscape conditions, societal risks, and management objectives. Analyses of observed and predicted firefighting resource use revealed reductions in the mean personnel resources used per wildfire per day during the pandemic for models developed across the western U.S. and for various western U.S. fire regions. Notably, the Northern California and the Great Basin Coordination Centers showed statistically significant reductions in ground personnel use during the COVID-19 pandemic. Learning from wildland fire management strategies and resource use trends that occurred during the COVID-19 pandemic, fire agencies can better anticipate resource constraints that may arise during the compounding threats of severe wildland fire activity and infectious disease outbreaks to proactively prepare and adapt suppression management strategies.