Blood pressure, executive function, and network connectivity in middle-aged adults at risk of dementia in late life.

Midlife blood pressure is associated with structural brain changes, cognitive decline, and dementia in late life. However, the relationship between early adulthood blood pressure exposure, brain structure and function, and cognitive performance in midlife is not known. A better understanding of these relationships in the preclinical stage may advance our mechanistic understanding of vascular contributions to late-life cognitive decline and dementia and may provide early therapeutic targets. To identify resting-state functional connectivity of executive control networks (ECNs), a group independent components analysis was performed of functional MRI scans of 600 individuals from the Coronary Artery Risk Development in Young Adults longitudinal cohort study, with cumulative systolic blood pressure (cSBP) measured at nine visits over the preceding 30 y. Dual regression analysis investigated performance-related connectivity of ECNs in 578 individuals (mean age 55.5 ± 3.6 y, 323 female, 243 Black) with data from the Stroop color-word task of executive function. Greater connectivity of a left ECN to the bilateral anterior gyrus rectus, right posterior orbitofrontal cortex, and nucleus accumbens was associated with better executive control performance on the Stroop. Mediation analyses showed that while the relationship between cSBP and Stroop performance was mediated by white matter hyperintensities (WMH), resting-state connectivity of the ECN mediated the relationship between WMH and executive function. Increased connectivity of the left ECN to regions involved in reward processing appears to compensate for the deleterious effects of WMH on executive function in individuals across the burden of cumulative systolic blood pressure exposure in midlife.

Multiscale functional connectivity patterns of the aging brain learned from harmonized rsfMRI data of the multi-cohort iSTAGING study.

To learn multiscale functional connectivity patterns of the aging brain, we built a brain age prediction model of functional connectivity measures at seven scales on a large fMRI dataset, consisting of resting-state fMRI scans of 4186 individuals with a wide age range (22 to 97 years, with an average of 63) from five cohorts. We computed multiscale functional connectivity measures of individual subjects using a personalized functional network computational method, harmonized the functional connectivity measures of subjects from multiple datasets in order to build a functional brain age model, and finally evaluated how functional brain age gap correlated with cognitive measures of individual subjects. Our study has revealed that functional connectivity measures at multiple scales were more informative than those at any single scale for the brain age prediction, the data harmonization significantly improved the brain age prediction performance, and the data harmonization in the functional connectivity measures' tangent space worked better than in their original space. Moreover, brain age gap scores of individual subjects derived from the brain age prediction model were significantly correlated with clinical and cognitive measures. Overall, these results demonstrated that multiscale functional connectivity patterns learned from a large-scale multi-site rsfMRI dataset were informative for characterizing the aging brain and the derived brain age gap was associated with cognitive and clinical measures.

Deep Generative Medical Image Harmonization for Improving Cross-Site Generalization in Deep Learning Predictors.

BACKGROUND: In the medical imaging domain, deep learning-based methods have yet to see widespread clinical adoption, in part due to limited generalization performance across different imaging devices and acquisition protocols. The deviation between estimated brain age and biological age is an established biomarker of brain health and such models may benefit from increased cross-site generalizability. PURPOSE: To develop and evaluate a deep learning-based image harmonization method to improve cross-site generalizability of deep learning age prediction. STUDY TYPE: Retrospective. POPULATION: Eight thousand eight hundred and seventy-six subjects from six sites. Harmonization models were trained using all subjects. Age prediction models were trained using 2739 subjects from a single site and tested using the remaining 6137 subjects from various other sites. FIELD STRENGTH/SEQUENCE: Brain imaging with magnetization prepared rapid acquisition with gradient echo or spoiled gradient echo sequences at 1.5 T and 3 T. ASSESSMENT: StarGAN v2, was used to perform a canonical mapping from diverse datasets to a reference domain to reduce site-based variation while preserving semantic information. Generalization performance of deep learning age prediction was evaluated using harmonized, histogram matched, and unharmonized data. STATISTICAL TESTS: Mean absolute error (MAE) and Pearson correlation between estimated age and biological age quantified the performance of the age prediction model. RESULTS: Our results indicated a substantial improvement in age prediction in out-of-sample data, with the overall MAE improving from 15.81 (±0.21) years to 11.86 (±0.11) with histogram matching to 7.21 (±0.22) years with generative adversarial network (GAN)-based harmonization. In the multisite case, across the 5 out-of-sample sites, MAE improved from 9.78 (±6.69) years to 7.74 (±3.03) years with histogram normalization to 5.32 (±4.07) years with GAN-based harmonization. DATA CONCLUSION: While further research is needed, GAN-based medical image harmonization appears to be a promising tool for improving cross-site deep learning generalization. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 1.

Sorption of Strontium to Uraninite and Uranium(IV)-Silicate Nanoparticles.

Spent nuclear fuel contains both uranium (U) and high yield fission products, including strontium-90 (90Sr), a key radioactive contaminant at nuclear facilities. Both U and 90Sr will be present where spent nuclear fuel has been processed, including in storage ponds and tanks. However, the interactions between Sr and U phases under ambient conditions are not well understood. Over a pH range of 4-14, we investigate Sr sorption behavior in contact with two nuclear fuel cycle relevant U(IV) phases: nano-uraninite (UO2) and U(IV)-silicate nanoparticles. Nano-UO2 is a product of the anaerobic corrosion of metallic uranium fuel, and UO2 is also the predominant form of U in ceramic fuels. U(IV)-silicates form stable colloids under the neutral to alkaline pH conditions highly relevant to nuclear fuel storage ponds and geodisposal scenarios. In sorption experiments, Sr had the highest affinity for UO2, although significant Sr sorption also occurred to U(IV)-silicate phases at pH ≥ 6. Extended X-ray absorption fine structure (EXAFS) spectroscopy, transmission electron microscopy, and desorption data for the UO2 system suggested that Sr interacted with UO2 via a near surface, highly coordinated complex at pH ≥ 10. EXAFS measurements for the U(IV)-silicate samples showed outer-sphere Sr sorption dominated at acidic and near-neutral pH with intrinsic Sr-silicates forming at pH ≥ 12. These complex interactions of Sr with important U(IV) phases highlight a largely unrecognized control on 90Sr mobility in environments of relevance to spent nuclear fuel management and storage.

Hydrotalcite Colloidal Stability and Interactions with Uranium(VI) at Neutral to Alkaline pH.

In the United Kingdom, decommissioning of legacy spent fuel storage facilities involves the retrieval of radioactive sludges that have formed as a result of corrosion of Magnox nuclear fuel. Retrieval of sludges may re-suspend a colloidal fraction of the sludge, thereby potentially enhancing the mobility of radionuclides including uranium. The colloidal properties of the layered double hydroxide (LDH) phase hydrotalcite, a key product of Magnox fuel corrosion, and its interactions with U(VI) are of interest. This is because colloidal hydrotalcite is a potential transport vector for U(VI) under the neutral-to-alkaline conditions characteristic of the legacy storage facilities and other nuclear decommissioning scenarios. Here, a multi-technique approach was used to investigate the colloidal stability of hydrotalcite and the U(VI) sorption mechanism(s) across pH 7-11.5 and with variable U(VI) surface loadings (0.01-1 wt %). Overall, hydrotalcite was found to form stable colloidal suspensions between pH 7 and 11.5, with some evidence for Mg2+ leaching from hydrotalcite colloids at pH ≤ 9. For systems with U present, >98% of U(VI) was removed from the solution in the presence of hydrotalcite, regardless of pH and U loading, although the sorption mode was affected by both pH and U concentrations. Under alkaline conditions, U(VI) surface precipitates formed on the colloidal hydrotalcite nanoparticle surface. Under more circumneutral conditions, Mg2+ leaching from hydrotalcite and more facile exchange of interlayer carbonate with the surrounding solution led to the formation of uranyl carbonate species (e.g., Mg(UO2(CO3)3)2-(aq)). Both X-ray absorption spectroscopy (XAS) and luminescence analysis confirmed that these negatively charged species sorbed as both outer- and inner-sphere tertiary complexes on the hydrotalcite surface. These results demonstrate that hydrotalcite can form pseudo-colloids with U(VI) under a wide range of pH conditions and have clear implications for understanding the uranium behavior in environments where hydrotalcite and other LDHs may be present.

White matter hyperintensities and imaging patterns of brain ageing in the general population.

White matter hyperintensities are associated with increased risk of dementia and cognitive decline. The current study investigates the relationship between white matter hyperintensities burden and patterns of brain atrophy associated with brain ageing and Alzheimer's disease in a large populatison-based sample (n = 2367) encompassing a wide age range (20-90 years), from the Study of Health in Pomerania. We quantified white matter hyperintensities using automated segmentation and summarized atrophy patterns using machine learning methods resulting in two indices: the SPARE-BA index (capturing age-related brain atrophy), and the SPARE-AD index (previously developed to capture patterns of atrophy found in patients with Alzheimer's disease). A characteristic pattern of age-related accumulation of white matter hyperintensities in both periventricular and deep white matter areas was found. Individuals with high white matter hyperintensities burden showed significantly (P < 0.0001) lower SPARE-BA and higher SPARE-AD values compared to those with low white matter hyperintensities burden, indicating that the former had more patterns of atrophy in brain regions typically affected by ageing and Alzheimer's disease dementia. To investigate a possibly causal role of white matter hyperintensities, structural equation modelling was used to quantify the effect of Framingham cardiovascular disease risk score and white matter hyperintensities burden on SPARE-BA, revealing a statistically significant (P < 0.0001) causal relationship between them. Structural equation modelling showed that the age effect on SPARE-BA was mediated by white matter hyperintensities and cardiovascular risk score each explaining 10.4% and 21.6% of the variance, respectively. The direct age effect explained 70.2% of the SPARE-BA variance. Only white matter hyperintensities significantly mediated the age effect on SPARE-AD explaining 32.8% of the variance. The direct age effect explained 66.0% of the SPARE-AD variance. Multivariable regression showed significant relationship between white matter hyperintensities volume and hypertension (P = 0.001), diabetes mellitus (P = 0.023), smoking (P = 0.002) and education level (P = 0.003). The only significant association with cognitive tests was with the immediate recall of the California verbal and learning memory test. No significant association was present with the APOE genotype. These results support the hypothesis that white matter hyperintensities contribute to patterns of brain atrophy found in beyond-normal brain ageing in the general population. White matter hyperintensities also contribute to brain atrophy patterns in regions related to Alzheimer's disease dementia, in agreement with their known additive role to the likelihood of dementia. Preventive strategies reducing the odds to develop cardiovascular disease and white matter hyperintensities could decrease the incidence or delay the onset of dementia.

Association of early left ventricular dysfunction with advanced magnetic resonance white matter and gray matter brain measures: The CARDIA study.

INTRODUCTION: Relations between heart failure and clinically manifested stroke are well known, but the associations between heart and brain early abnormalities are not totally clear. AIMS: We explore relations of subclinical brain abnormalities with early cardiac dysfunction in a large healthy middle-aged biracial cohort. METHODS: The CARDIA study enrolled 5115 young adults aged 18-30 years at baseline (1985-1986). We assessed 719 Caucasian and African American participants of the CARDIA study, with echocardiograms and brain MRI at follow-up year 25 (2010-2011). Echocardiography assessed aortic root diameter; LVEF; circumferential, longitudinal, and radial deformation. Cerebral MRI DTI, and, on a subset, ASL perfusion sequences were used to assess white matter fractional anisotropy and gray matter cerebral blood flow (CBF). Linear regression explored relations between cardiac parameters and cerebral measures, adjusting for anthropometrics, risk factors, and brain constitutional variation. RESULTS: Mean age 50 ± 4 years, SBP 118 ± 15 mm Hg; 60% white, and 48% men. Mean CBF was 46 ± 9 mL/100 g/min, and white matter fractional anisotropy was 0.31 ± 0.02. Worse circumferential deformation and larger aortic root were related to worse white matter fractional anisotropy. Worse radial systolic deformation was related to worse CBF in multivariable models. LVEF did not relate to early brain abnormalities. CONCLUSIONS: In spite of no apparent effect of LV ejection fraction, early subclinical cardiac dysfunction and brain abnormalities are present and associated in middle-aged generally healthy individuals.

Identifying Patients for Intensive Blood Pressure Treatment Based on Cognitive Benefit: A Secondary Analysis of the SPRINT Randomized Clinical Trial.

Importance: Intensive vs standard treatment to lower systolic blood pressure (SBP) reduces risk of mild cognitive impairment (MCI) or dementia; however, the magnitude of cognitive benefit likely varies among patients. Objective: To estimate the magnitude of cognitive benefit of intensive vs standard systolic BP (SBP) treatment. Design, Setting, and Participants: In this ad hoc secondary analysis of the Systolic Blood Pressure Intervention Trial (SPRINT), 9361 randomized clinical trial participants 50 years or older with high cardiovascular risk but without a history of diabetes, stroke, or dementia were followed up. The SPRINT trial was conducted between November 1, 2010, and August 31, 2016, and the present analysis was completed on October 31, 2022. Intervention: Systolic blood pressure treatment to an intensive (<120 mm Hg) vs standard (<140 mm Hg) target. Main Outcomes and Measures: The primary outcome was a composite of adjudicated probable dementia or amnestic MCI. Results: A total of 7918 SPRINT participants were included in the analysis; 3989 were in the intensive treatment group (mean [SD] age, 67.9 [9.2] years; 2570 [64.4%] men; 1212 [30.4%] non-Hispanic Black) and 3929 were in the standard treatment group (mean [SD] age, 67.9 [9.4] years; 2570 [65.4%] men; 1249 [31.8%] non-Hispanic Black). Over a median follow-up of 4.13 (IQR, 3.50-5.88) years, there were 765 and 828 primary outcome events in the intensive treatment group and standard treatment group, respectively. Older age (hazard ratio [HR] per 1 SD, 1.87 [95% CI, 1.78-1.96]), Medicare enrollment (HR per 1 SD, 1.42 [95% CI, 1.35-1.49]), and higher baseline serum creatinine level (HR per 1 SD, 1.24 [95% CI, 1.19-1.29]) were associated with higher risk of the primary outcome, while better baseline cognitive functioning (HR per 1 SD, 0.43 [95% CI, 0.41-0.44]) and active employment status (HR per 1 SD, 0.44 [95% CI, 0.42-0.46]) were associated with lower risk of the primary outcome. Risk of the primary outcome by treatment goal was estimated accurately based on similar projected and observed absolute risk differences (C statistic = 0.79). Higher baseline risk for the primary outcome was associated with greater benefit (ie, larger absolute reduction of probable dementia or amnestic MCI) of intensive vs standard treatment across the full range of estimated baseline risk. Conclusions and Relevance: In this secondary analysis of the SPRINT trial, participants with higher baseline projected risk of probable dementia or amnestic MCI gained greater absolute cognitive benefit from intensive vs standard SBP treatment in a monotonic fashion. Trial Registration: ClinicalTrials.gov Identifier: NCT01206062.

Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures.

Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing pathologies. MRI and, more recently, AI methods have been instrumental in understanding the neuroanatomical changes that occur during aging in large and diverse populations. However, the multiplicity and mutual overlap of both pathologic processes and affected brain regions make it difficult to precisely characterize the underlying neurodegenerative profile of an individual from an MRI scan. Herein, we leverage a state-of-the art deep representation learning method, Surreal-GAN, and present both methodological advances and extensive experimental results that allow us to elucidate the heterogeneity of brain aging in a large and diverse cohort of 49,482 individuals from 11 studies. Five dominant patterns of neurodegeneration were identified and quantified for each individual by their respective (herein referred to as) R-indices. Significant associations between R-indices and distinct biomedical, lifestyle, and genetic factors provide insights into the etiology of observed variances. Furthermore, baseline R-indices showed predictive value for disease progression and mortality. These five R-indices contribute to MRI-based precision diagnostics, prognostication, and may inform stratification into clinical trials.

The effect of humic acid on uranyl sorption onto bentonite at trace uranium levels.

The effect of humic acid (HA) on U(VI) sorption on bentonite was studied in batch experiments at room temperature and ambient atmosphere at a (237)U(VI) concentration of 8.4 × 10(-11) M and HA concentration of 100 mg L(-1). The distribution of U(VI) between the liquid and solid phases was studied as a function of pH and ionic strength both in the absence and presence of HA. It was shown that the uranyl sorption on bentonite is strongly dependent on pH and the presence of humics, and the effect of the addition order was negligible. In the absence of HA an enhancement in the uptake with increasing pH was observed and a sharp sorption edge was found to take place between pH 3.2 and 4.2. The presence of HA slightly increases uranium(VI) sorption at low pH and curtails it at moderate pH, compared to the absence of HA. In the basic pH range for both the presence and absence of HA the sorption of uranium is significantly reduced, which could be attributed to the formation of soluble uranyl carbonate complexes. The influence of ionic strength on U(VI) and HA uptake by bentonite were investigated in the range of 0.01-1.0 M, and while there was an enhancement in the sorption of humic acid with increasing ionic strength, no significant effect of the ionic strength on the U(VI) sorption was observed in both the absence and presence of HA.

Higher literacy is associated with better white matter integrity and cognition in middle age.

Introduction: Literacy can be a better measure of quality of education. Its association with brain health in midlife has not been thoroughly investigated. Methods: We studied, cross-sectionally, 616 middle-aged adults (mean age of 55.1 ± 3.6 years, 53% female and 38% Black) from the Coronary Artery Risk Development in Young Adults (CARDIA) study. We correlated literacy with cognitive tests, gray matter volumes, and fractional anisotropy (FA) values (indirect measures of white matter integrity) using linear regression. Results: The higher-literacy group (n = 499) performed better than the low-literacy group (n = 117) on all cognitive tests. There was no association between literacy and gray matter volumes. The higher-literacy group had greater total-brain FA and higher temporal, parietal, and occipital FA values after multivariable adjustments. Discussion: Higher literacy is associated with higher white matter integrity as well as with better cognitive performance in middle-aged adults. These results highlight the importance of focusing on midlife interventions to improve literacy skills.

Association of Cerebral Blood Flow With Longitudinal Changes in Cerebral Microstructural Integrity in the Coronary Artery Risk Development in Young Adults (CARDIA) Study.

Importance: Decreased cerebral tissue integrity and cerebral blood flow (CBF) are features of neurodegenerative diseases. Brain tissue maintenance is an energy-demanding process, making it particularly sensitive to hypoperfusion. However, little is known about the association between blood flow and brain microstructural integrity, including in normative aging. Objective: To assess associations between CBF and changes in cerebral tissue integrity in white matter and gray matter brain regions. Design, Setting, and Participants: In this longitudinal cohort study, magnetic resonance imaging was performed on 732 healthy adults from the Coronary Artery Risk Development in Young Adults (CARDIA) study, a prospective longitudinal study (baseline age of 18-30 years) that examined participants up to 8 times during 30 years (1985-1986 to 2015-2016). Cerebral blood flow was measured at baseline (year 25 of the CARDIA study), and changes in diffusion tensor indices of fractional anisotropy (FA) and mean diffusivity (MD), measures of microstructural tissue integrity, were measured at both baseline and after approximately 5 years of follow-up (year 30). Analyses were conducted from November 5, 2020, to January 29, 2022. Main Outcomes and Measures: Automated algorithms and linear mixed-effects statistical models were used to evaluate the associations between CBF at baseline and changes in FA or MD. Results: After exclusion of participants with missing or low-quality data, 654 at baseline (342 women; mean [SD] age, 50.3 [3.5] years) and 433 at follow-up (230 women; mean [SD] age, 55.1 [3.5] years) were scanned for CBF or FA and MD imaging. In the baseline cohort, 247 participants were Black (37.8%) and 394 were White (60.2%); in the follow-up cohort, 156 were Black (36.0%) and 277 were White (64.0%). Cross-sectionally, FA and MD were associated with CBF in most regions evaluated, with lower CBF values associated with lower FA or higher MD values, including the frontal white matter lobes (for CBF and MD: mean [SE] ß = -1.4 [0.5] × 10-6; for CBF and FA: mean [SE] ß = 2.9 [1.0] × 10-4) and the parietal white matter lobes (for CBF and MD: mean [SE] ß = -2.4 [0.6] × 10-6; for CBF and FA: mean [SE] ß = 4.4 [1.1] × 10-4). Lower CBF values at baseline were also significantly associated with steeper regional decreases in FA or increases in MD in most brain regions investigated, including the frontal (for CBF and MD: mean [SE] ß = -1.1 [0.6] × 10-6; for CBF and FA: mean [SE] ß = 2.9 [1.0] × 10-4) and parietal lobes (for CBF and MD: mean [SE] ß = -1.5 [0.7] × 10-6; for CBF and FA: mean [SE] ß = 4.4 [1.1] × 10-4). Conclusions and Relevance: Results of this longitudinal cohort study of the association between CBF and diffusion tensor imaging metrics suggest that blood flow may be significantly associated with brain tissue microstructure. This work may lay the foundation for investigations to clarify the nature of early brain damage in neurodegeneration. Such studies may lead to new neuroimaging biomarkers of brain microstructure and function for disease progression.

Disentangling Alzheimer's disease neurodegeneration from typical brain ageing using machine learning.

Neuroimaging biomarkers that distinguish between changes due to typical brain ageing and Alzheimer's disease are valuable for determining how much each contributes to cognitive decline. Supervised machine learning models can derive multivariate patterns of brain change related to the two processes, including the Spatial Patterns of Atrophy for Recognition of Alzheimer's Disease (SPARE-AD) and of Brain Aging (SPARE-BA) scores investigated herein. However, the substantial overlap between brain regions affected in the two processes confounds measuring them independently. We present a methodology, and associated results, towards disentangling the two. T1-weighted MRI scans of 4054 participants (48-95 years) with Alzheimer's disease, mild cognitive impairment (MCI), or cognitively normal (CN) diagnoses from the Imaging-based coordinate SysTem for AGIng and NeurodeGenerative diseases (iSTAGING) consortium were analysed. Multiple sets of SPARE scores were investigated, in order to probe imaging signatures of certain clinically or molecularly defined sub-cohorts. First, a subset of clinical Alzheimer's disease patients (n = 718) and age- and sex-matched CN adults (n = 718) were selected based purely on clinical diagnoses to train SPARE-BA1 (regression of age using CN individuals) and SPARE-AD1 (classification of CN versus Alzheimer's disease) models. Second, analogous groups were selected based on clinical and molecular markers to train SPARE-BA2 and SPARE-AD2 models: amyloid-positive Alzheimer's disease continuum group (n = 718; consisting of amyloid-positive Alzheimer's disease, amyloid-positive MCI, amyloid- and tau-positive CN individuals) and amyloid-negative CN group (n = 718). Finally, the combined group of the Alzheimer's disease continuum and amyloid-negative CN individuals was used to train SPARE-BA3 model, with the intention to estimate brain age regardless of Alzheimer's disease-related brain changes. The disentangled SPARE models, SPARE-AD2 and SPARE-BA3, derived brain patterns that were more specific to the two types of brain changes. The correlation between the SPARE-BA Gap (SPARE-BA minus chronological age) and SPARE-AD was significantly reduced after the decoupling (r = 0.56-0.06). The correlation of disentangled SPARE-AD was non-inferior to amyloid- and tau-related measurements and to the number of APOE ε4 alleles but was lower to Alzheimer's disease-related psychometric test scores, suggesting the contribution of advanced brain ageing to the latter. The disentangled SPARE-BA was consistently less correlated with Alzheimer's disease-related clinical, molecular and genetic variables. By employing conservative molecular diagnoses and introducing Alzheimer's disease continuum cases to the SPARE-BA model training, we achieved more dissociable neuroanatomical biomarkers of typical brain ageing and Alzheimer's disease.

Mid-life epigenetic age, neuroimaging brain age, and cognitive function: coronary artery risk development in young adults (CARDIA) study.

The proportion of aging populations affected by dementia is increasing. There is an urgent need to identify biological aging markers in mid-life before symptoms of age-related dementia present for early intervention to delay the cognitive decline and the onset of dementia. In this cohort study involving 1,676 healthy participants (mean age 40) with up to 15 years of follow up, we evaluated the associations between cognitive function and two classes of novel biological aging markers: blood-based epigenetic aging and neuroimaging-based brain aging. Both accelerated epigenetic aging and brain aging were prospectively associated with worse cognitive outcomes. Specifically, every year faster epigenetic or brain aging was on average associated with 0.19-0.28 higher (worse) Stroop score, 0.04-0.05 lower (worse) RAVLT score, and 0.23-0.45 lower (worse) DSST (all false-discovery-rate-adjusted p <0.05). While epigenetic aging is a more stable biomarker with strong long-term predictive performance for cognitive function, brain aging biomarker may change more dynamically in temporal association with cognitive decline. The combined model using epigenetic and brain aging markers achieved the highest accuracy (AUC: 0.68, p<0.001) in predicting global cognitive function status. Accelerated epigenetic age and brain age at midlife may aid timely identification of individuals at risk for accelerated cognitive decline and promote the development of interventions to preserve optimal functioning across the lifespan.

Risk of Mild Cognitive Impairment or Probable Dementia in New Users of Angiotensin II Receptor Blockers and Angiotensin-Converting Enzyme Inhibitors: A Secondary Analysis of Data From the Systolic Blood Pressure Intervention Trial (SPRINT).

Importance: The cardiovascular and renal outcomes of angiotensin-II receptor blocker (ARB) and angiotensin-converting enzyme inhibitor (ACEI) treatment are well-known; however, few studies have evaluated initiation of these agents and cognitive impairment. Objective: To emulate a target trial to evaluate the cognitive outcomes of initiating an ARB- vs ACEI-based antihypertensive regimen in individuals at risk for mild cognitive impairment (MCI) and probable dementia (PD). Design, Setting, and Participants: Active comparator, new-user observational cohort study design using data from the Systolic Blood Pressure Intervention Trial (SPRINT), conducted November 2010 through July 2018. Marginal cause-specific hazard ratios (HRs) and treatment-specific cumulative incidence functions were estimated with inverse probability (IP) weighting to account for confounding. Participants were using neither an ARB nor ACEI at baseline. Data analysis was conducted from April 7, 2021, to April 26, 2022. Exposures: New users of ARB vs ACEI during the first 12 months of trial follow-up. Main Outcomes and Measures: Composite of adjudicated amnestic MCI or PD. Results: Of 9361 participants, 727 and 1313 new users of an ARB or ACEI, respectively, with well-balanced baseline characteristics between medication exposure groups after inverse probability weighting (mean [SD] age, 67 [9.5] years; 1291 ]63%] male; 240 [33%] Black; 89 [12%] Hispanic; 383 [53%] White; and 15 [2%] other race or ethnicity. In the primary analysis, during a median follow-up of 4.9 years, the inverse probability-weighted rate of amnestic MCI or PD was 4.3 vs 4.6 per 100 person-years among participants initiating ARB vs ACEI (HR, 0.93; 95% CI, 0.76-1.13). In subgroup analyses, new users of an ARB vs ACEI had a lower rate of amnestic MCI or PD among those in the standard systolic blood pressure treatment arm (HR, 0.61; 95% CI, 0.41-0.91) but not in the intensive arm (HR, 1.17; 95% CI, 0.90-1.52) (P = .007 for interaction). Conclusions and Relevance: In this observational cohort study of US adults at high cardiovascular disease risk, there was no difference in the rate of amnestic MCI or PD among new users of an ARB compared with ACEI, although 95% CIs were wide.

Association of Antihypertensives That Stimulate vs Inhibit Types 2 and 4 Angiotensin II Receptors With Cognitive Impairment.

Importance: Use of antihypertensive medications that stimulate type 2 and 4 angiotensin II receptors, compared with those that do not stimulate these receptors, has been associated with a lower risk of dementia. However, this association with cognitive outcomes in hypertension trials, with blood pressure levels in the range of current guidelines, has not been evaluated. Objective: To examine the association between use of exclusively antihypertensive medication regimens that stimulate vs inhibit type 2 and 4 angiotensin II receptors on mild cognitive impairment (MCI) or dementia. Design, Setting, and Participants: This cohort study is a secondary analysis (April 2011 to July 2018) of participants in the randomized Systolic Blood Pressure Intervention Trial (SPRINT), which recruited individuals 50 years or older with hypertension and increased cardiovascular risk but without a history of diabetes, stroke, or dementia. Data analysis was conducted from March 16 to July 6, 2021. Exposures: Prevalent use of angiotensin II receptor type 2 and 4-stimulating or -inhibiting antihypertensive medication regimens at the 6-month study visit. Main Outcomes and Measures: The primary outcome was a composite of adjudicated amnestic MCI or probable dementia. Results: Of the 8685 SPRINT participants who were prevalent users of antihypertensive medication regimens at the 6-month study visit (mean [SD] age, 67.7 [11.2] years; 5586 [64.3%] male; and 935 [10.8%] Hispanic, 2605 [30.0%] non-Hispanic Black, 4983 [57.4%] non-Hispanic White, and 162 [1.9%] who responded as other race or ethnicity), 2644 (30.4%) were users of exclusively stimulating, 1536 (17.7%) inhibiting, and 4505 (51.9%) mixed antihypertensive medication regimens. During a median of 4.8 years of follow-up (95% CI, 4.7-4.8 years), there were 45 vs 59 cases per 1000 person-years of amnestic MCI or probable dementia among prevalent users of regimens that contained exclusively stimulating vs inhibiting antihypertensive medications (hazard ratio [HR], 0.76; 95% CI, 0.66-0.87). When comparing stimulating-only vs inhibiting-only users, amnestic MCI occurred at rates of 40 vs 54 cases per 1000 person-years (HR, 0.74; 95% CI, 0.64-0.87) and probable dementia at rates of 8 vs 10 cases per 1000 person-years (HR, 0.80; 95% CI, 0.57-1.14). Negative control outcome analyses suggested the presence of residual confounding. Conclusions and Relevance: In this secondary analysis of SPRINT, prevalent users of regimens that contain exclusively antihypertensive medications that stimulate vs inhibit type 2 and 4 angiotensin II receptors had lower rates of incident cognitive impairment. Residual confounding cannot be ruled out. If these results are replicated in randomized clinical trials, certain antihypertensive medications could be prioritized to prevent cognitive decline.

Estimation of Model VII humic binding constants for Pd2+, Sn2+, U4+, NpO2(2+), Pu4+ and PuO2(2+).

Using previously established procedures that utilise linear free energy relationships, we estimated binding constants for the Windermere Humic Aqueous Model VII (WHAM/Model VII) for several radionuclide cations (Pd(2+), Sn(2+), U(4+), NpO(2)(2+), Pu(4+) and PuO(2)(2+)). This extends the number of cations that can be calculated with the model above the 40 included in the original Model VII work. When combined with equilibrium constants for inorganic species this allows the calculation of equilibrium distributions of chemical species under a wide range of conditions.

Effect of humic acid & bacterial exudates on sorption-desorption interactions of 90Sr with brucite.

One of the nuclear fuel storage ponds at Sellafield (United Kingdom) is open to the air, and has contained a significant inventory of corroded magnox fuel and sludge for several decades. As a result, some fission products have also been released into solution. 90Sr is known to constitute a small mass of the radionuclides present in the pond, but due to its solubility and activity, it is at risk of challenging effluent discharge limits. The sludge is predominantly composed of brucite (Mg(OH)2), and organic molecules are known to be present in the pond liquor with occasional algal blooms restricting visibility. Understanding the chemical interactions of these components is important to inform ongoing sludge retrievals and effluent management. Additionally, interactions of radionuclides with organics at high pH will be an important consideration for the evolution of cementitious backfilled disposal sites in the UK. Batch sorption-desorption experiments were performed with brucite, 90Sr and natural organic matter (NOM) (humic acid (HA) and Pseudanabaena catenata cyanobacterial growth supernatant) in both binary and ternary systems at high pH. Ionic strength, pH and order of addition of components were varied. 90Sr was shown not to interact strongly with the bulk brucite surface in binary systems under pH conditions relevant to the pond. HA in both binary and ternary systems demonstrated a strong affinity for the brucite surface. Ternary systems containing HA demonstrated enhanced sorption of 90Sr at pH 11.5 and vice versa, likely via formation of strontium-humate complexes regardless of the order of addition of components. The distribution coefficients show HA sorption to be reversible at all pH values studied, and it appeared to control 90Sr behaviour at pH 11.5. Ternary systems containing cyanobacterial supernatant demonstrated a difference in 90Sr behaviour when the culture had been subjected to irradiation in the first stages of its growth.

N-Terminal pro-Brain Natriuretic Peptide and Associations With Brain Magnetic Resonance Imaging (MRI) Features in Middle Age: The CARDIA Brain MRI Study.

OBJECTIVE: As part of research on the heart-brain axis, we investigated the association of N-terminal pro-brain natriuretic peptide (NT-proBNP) with brain structure and function in a community-based cohort of middle-aged adults from the Brain Magnetic Resonance Imaging sub-study of the Coronary Artery Risk Development in Young Adults (CARDIA) Study. APPROACH AND RESULTS: In a cohort of 634 community-dwelling adults with a mean (range) age of 50.4 (46-52) years, we examined the cross-sectional association of NT-proBNP to total, gray (GM) and white matter (WM) volumes, abnormal WM load and WM integrity, and to cognitive function tests [the Digit Symbol Substitution Test (DSST), the Stroop test, and the Rey Auditory-Verbal Learning Test]. These associations were examined using linear regression models adjusted for demographic and cardiovascular risk factors and cardiac output. Higher NT-proBNP concentration was significantly associated with smaller GM volume (ß = -3.44; 95% CI = -5.32, -0.53; p = 0.003), even after additionally adjusting for cardiac output (ß = -2.93; 95% CI = -5.32, -0.53; p = 0.017). Higher NT-proBNP levels were also associated with lower DSST scores. NT-proBNP was not related to WM volume, WM integrity, or abnormal WM load. CONCLUSION: In this middle-aged cohort, subclinical levels of NT-proBNP were related to brain function and specifically to GM and not WM measures, extending similar findings in older cohorts. Further research is warranted into biomarkers of cardiac dysfunction as a target for early markers of a brain at risk.

Regional tract-specific white matter hyperintensities are associated with patterns to aging-related brain atrophy via vascular risk factors, but also independently.

INTRODUCTION: We sought to investigate associations of regional white matter hyperintensities (WMHs) within white matter (WM) tracts with cardiovascular risk and brain aging-related atrophy throughout adulthood in the general population, leveraging state of the art pattern analysis methods. METHODS: We analyzed a large sample (n = 2367) from the Study of Health in Pomerania, Germany (range 20-90 years). WMHs were automatically segmented on T1-weighted and fluid-attenuated inversion recovery magnetic resonance images, and WMH volumes were calculated in WM regions defined using the John Hopkins University WM tractography atlas. Regions with the highest average WMH volume were selected. We calculated a subject-specific index, Spatial Pattern of Alteration for Recognition of Brain Aging, to measure age-related atrophy patterns. The Framingham cardiovascular disease risk score summarized the individual cardiovascular risk profile. We used structural equation models, independently for each region, using Spatial Pattern of Alteration for Recognition of Brain Aging as a dependent variable, age as an independent variable, and cardiovascular disease risk score and regional WMH volumes as mediators. RESULTS: Selected 12 WM regions included 75% of the total WMH burden in average. Structural equation models showed that the age effect on Spatial Pattern of Alteration for Recognition of Brain Aging was mediated by WMHs to a different extent in the superior frontal WM, anterior corona radiata, inferior frontal WM, superior corona radiata, superior longitudinal fasciculus, middle temporal WM, posterior corona radiata, superior parietal WM, splenium of corpus callosum, posterior thalamic radiation, and middle occipital WM (variance explained between 2.8% and 10.3%, P < .0001 Bonferroni corrected), but not in precentral WM. CONCLUSIONS: Our results indicate that WMHs, in most WM tracts, might accelerate the brain aging process throughout adulthood in the general population as a result of vascular risk factors, but also independent of them. Preventive strategies against WMHs (such as controlling vascular risk factors or microglia depletion) could delay brain aging.