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Consumption of Soya Isoflavones Improved Polycystic Ovary Syndrome (PCOS)-Associated Metabolic Disorders in a Rat Model
- Chao-Wu Xiao, Adriana A. Carbonel, Patricia D. A. Lima, Amy Hendry, Benjamin K. Tsang
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- Journal:
- British Journal of Nutrition / Accepted manuscript
- Published online by Cambridge University Press:
- 03 June 2024, pp. 1-25
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Polycystic ovary syndrome (PCOS) is associated with increased risks for certain metabolic disorders such as insulin resistance, non-alcoholic fatty liver disease (NAFLD), and suppressed ovarian follicular development. This study aimed to examine whether soya isoflavones (ISF) mitigate these PCOS-associated metabolic disorders in a rat model. Weanling Sprague-Dawley female rats were randomly divided into 6 groups and were treated with either 0 or 83 µg/day dihydrotestosterone (DHT) to induce PCOS and fed diets containing 0, 0.5, or 1g ISF/kg diet for 8 weeks. DHT treatment increased food intake, body weight gain (BWG, p<0.001), percentage of primordial follicles (60% vs 50.9%, p<0.05), and accumulation of lipid droplets in the livers. It also elevated serum total cholesterol (TC), free cholesterol (FC), triglycerides, non-esterified fatty acids (NEFA), and leptin, and hepatic TC and NEFA. Additionally, DHT treatment reduced the percentage of primary follicles (13.8% vs 30.2%, p<0.05), ovary weight, and length (p<0.001), as well as insulin sensitivity (p<0.01) compared to the Control. ISF intake at 1g/kg reduced BWG, serum TC, FC, NEFA, leptin, and hepatic triglycerides and DHT-induced insulin resistance (p<0.01). ISF intake at both levels decreased DHT-induced lipid droplet accumulation in the livers, and changes in the percentages of primordial and primary follicles. Dietary soya ISF alleviated DHT-induced BWG, insulin resistance, and hepatic lipid droplet accumulation, as well as suppressed ovarian follicular development. This suggests that consumption of soya foods or ISF supplements may be beneficial for the individuals with PCOS, mitigating the associated metabolic disorders such as diabetes and NAFLD.
A molecular perspective on the genera Paragonimus Braun, Euparagonimus Chen and Pagumogonimus Chen
- D. Blair, B. Wu, Z.S. Chang, X. Gong, T. Agatsuma, Y.N. Zhang, S.H. Chen, J.X. Lin, M.G. Chen, J. Waikagul, A.G. Guevara, Z. Feng, G.M. Davis
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- Journal:
- Journal of Helminthology / Volume 73 / Issue 4 / April 1999
- Published online by Cambridge University Press:
- 11 April 2024, pp. 295-299
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The status of the genera Euparagonimus Chen, 1963 and Pagumogonimus Chen, 1963 relative to Paragonimus Braun, 1899 was investigated using DNA sequences from the mitochondrial cytochrome c oxidase subunit I (CO1) gene (partial) and the nuclear ribosomal DNA second internal transcribed spacer (ITS2). In the phylogenetic trees constructed, the genus Pagumogonimus is clearly not monophyletic and therefore not a natural taxon. Indeed, the type species of Pagumogonimus,P. skrjabini from China, is very closely related to Paragonimus miyazakii from Japan. The status of Euparagonimus is less obvious. Euparagonimus cenocopiosus lies distant from other lungflukes included in the analysis. It can be placed as sister to Paragonimus in some analyses and falls within the genus in others. A recently published morphological study placed E. cenocopiosus within the genus Paragonimus and probably this is where it should remain.
19 - Decision-Making Regarding Child Victims and Witnesses
- from Part II - Pretrial Phase Decision-Making
- Edited by Monica K. Miller, University of Nevada, Reno, Logan A. Yelderman, Prairie View A & M University, Texas, Matthew T. Huss, Creighton University, Omaha, Jason A. Cantone, George Mason University, Virginia
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- Book:
- The Cambridge Handbook of Psychology and Legal Decision-Making
- Published online:
- 22 February 2024
- Print publication:
- 29 February 2024, pp 290-306
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Summary
Children are a critical part of certain legal trials, such as cases involving child abuse and neglect, and especially in cases of child sexual abuse. It is common for the only evidence in these types of cases to be the statement of the child victims. Children’s decisions about if and when to disclose the abuse are affected by many factors, and delays in disclosure are common. Police, forensic interviewers, prosecutors, and other professionals make decisions about when and how to interview children, the accuracy/credibility of their statements, if a case will move forward, and if and how children will testify in court. In some courtrooms, children are given special accommodations (e.g., testifying through closed-circuit TV or being accompanied by a therapy dog). Decisions about evaluating children in these situations have implications for the safety of children and the protection of innocent adults. Future research and policy implications are discussed.
Fixed-time anti-saturation control with concise system structure for the 6-DOF motion of spacecraft
- X. Wei, Y. Tian, S. Wu, D. Zhang, X. Shao, L. Chen
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- The Aeronautical Journal , First View
- Published online by Cambridge University Press:
- 21 February 2024, pp. 1-25
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This paper proposes a fixed-time anti-saturation (FT-AS) control scheme with a simple control loop for the 6-Degree-of-Freedom tracking (6-DOF) control problem of spacecraft with parameter uncertainties, external disturbances and input saturation. Considering the external disturbance and parameter uncertainties, the dynamical model of the tracking error is established. The traditional methods of handling input saturation usually add anti-saturation subsystems in the control system to suppress the impact of input overshoot. However, this paper directly inputs the input overshoot into the tracking error model, thus constructing a modified lumped disturbance term that includes the influence of input overshoot. Then, a novel fixed-time disturbance observer (FT-DO) is designed to estimate and compensate for this modified lumped disturbance. Therefore, there is no need to add the anti-saturation structures in the control loop, significantly reducing the complexity of the system. Finally, an observer-based fixed-time non-singular terminal sliding mode (FT-NTSM) controller is designed to guarantee the fixed-time stability of the whole system. In this way, the convergence time of the proposed scheme does not depend on the system’s initial conditions. Simulation results illustrate that the proposed method keeps the control input within the limit while achieving high-precision tracking control of attitude and position.
53 2-Back Performance Does Not Differ Between Cognitive Training Groups in Older Adults Without Dementia
- Nicole D Evangelista, Jessica N Kraft, Hanna K Hausman, Andrew O’Shea, Alejandro Albizu, Emanuel M Boutzoukas, Cheshire Hardcastle, Emily J Van Etten, Pradyumna K Bharadwaj, Hyun Song, Samantha G Smith, Steven DeKosky, Georg A Hishaw, Samuel Wu, Michael Marsiske, Ronald Cohen, Gene E Alexander, Eric Porges, Adam J Woods
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 360-361
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Objective:
Cognitive training is a non-pharmacological intervention aimed at improving cognitive function across a single or multiple domains. Although the underlying mechanisms of cognitive training and transfer effects are not well-characterized, cognitive training has been thought to facilitate neural plasticity to enhance cognitive performance. Indeed, the Scaffolding Theory of Aging and Cognition (STAC) proposes that cognitive training may enhance the ability to engage in compensatory scaffolding to meet task demands and maintain cognitive performance. We therefore evaluated the effects of cognitive training on working memory performance in older adults without dementia. This study will help begin to elucidate non-pharmacological intervention effects on compensatory scaffolding in older adults.
Participants and Methods:48 participants were recruited for a Phase III randomized clinical trial (Augmenting Cognitive Training in Older Adults [ACT]; NIH R01AG054077) conducted at the University of Florida and University of Arizona. Participants across sites were randomly assigned to complete cognitive training (n=25) or an education training control condition (n=23). Cognitive training and the education training control condition were each completed during 60 sessions over 12 weeks for 40 hours total. The education training control condition involved viewing educational videos produced by the National Geographic Channel. Cognitive training was completed using the Posit Science Brain HQ training program, which included 8 cognitive training paradigms targeting attention/processing speed and working memory. All participants also completed demographic questionnaires, cognitive testing, and an fMRI 2-back task at baseline and at 12-weeks following cognitive training.
Results:Repeated measures analysis of covariance (ANCOVA), adjusted for training adherence, transcranial direct current stimulation (tDCS) condition, age, sex, years of education, and Wechsler Test of Adult Reading (WTAR) raw score, revealed a significant 2-back by training group interaction (F[1,40]=6.201, p=.017, η2=.134). Examination of simple main effects revealed baseline differences in 2-back performance (F[1,40]=.568, p=.455, η2=.014). After controlling for baseline performance, training group differences in 2-back performance was no longer statistically significant (F[1,40]=1.382, p=.247, η2=.034).
Conclusions:After adjusting for baseline performance differences, there were no significant training group differences in 2-back performance, suggesting that the randomization was not sufficient to ensure adequate distribution of participants across groups. Results may indicate that cognitive training alone is not sufficient for significant improvement in working memory performance on a near transfer task. Additional improvement may occur with the next phase of this clinical trial, such that tDCS augments the effects of cognitive training and results in enhanced compensatory scaffolding even within this high performing cohort. Limitations of the study include a highly educated sample with higher literacy levels and the small sample size was not powered for transfer effects analysis. Future analyses will include evaluation of the combined intervention effects of a cognitive training and tDCS on nback performance in a larger sample of older adults without dementia.
2 Higher White Matter Hyperintensity Load Adversely Affects Pre-Post Proximal Cognitive Training Performance in Healthy Older Adults
- Emanuel M Boutzoukas, Andrew O’Shea, Jessica N Kraft, Cheshire Hardcastle, Nicole D Evangelista, Hanna K Hausman, Alejandro Albizu, Emily J Van Etten, Pradyumna K Bharadwaj, Samantha G Smith, Hyun Song, Eric C Porges, Alex Hishaw, Steven T DeKosky, Samuel S Wu, Michael Marsiske, Gene E Alexander, Ronald Cohen, Adam J Woods
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 671-672
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Objective:
Cognitive training has shown promise for improving cognition in older adults. Aging involves a variety of neuroanatomical changes that may affect response to cognitive training. White matter hyperintensities (WMH) are one common age-related brain change, as evidenced by T2-weighted and Fluid Attenuated Inversion Recovery (FLAIR) MRI. WMH are associated with older age, suggestive of cerebral small vessel disease, and reflect decreased white matter integrity. Higher WMH load associates with reduced threshold for clinical expression of cognitive impairment and dementia. The effects of WMH on response to cognitive training interventions are relatively unknown. The current study assessed (a) proximal cognitive training performance following a 3-month randomized control trial and (b) the contribution of baseline whole-brain WMH load, defined as total lesion volume (TLV), on pre-post proximal training change.
Participants and Methods:Sixty-two healthy older adults ages 65-84 completed either adaptive cognitive training (CT; n=31) or educational training control (ET; n=31) interventions. Participants assigned to CT completed 20 hours of attention/processing speed training and 20 hours of working memory training delivered through commercially-available Posit Science BrainHQ. ET participants completed 40 hours of educational videos. All participants also underwent sham or active transcranial direct current stimulation (tDCS) as an adjunctive intervention, although not a variable of interest in the current study. Multimodal MRI scans were acquired during the baseline visit. T1- and T2-weighted FLAIR images were processed using the Lesion Segmentation Tool (LST) for SPM12. The Lesion Prediction Algorithm of LST automatically segmented brain tissue and calculated lesion maps. A lesion threshold of 0.30 was applied to calculate TLV. A log transformation was applied to TLV to normalize the distribution of WMH. Repeated-measures analysis of covariance (RM-ANCOVA) assessed pre/post change in proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures in the CT group compared to their ET counterparts, controlling for age, sex, years of education and tDCS group. Linear regression assessed the effect of TLV on post-intervention proximal composite and sub-composite, controlling for baseline performance, intervention assignment, age, sex, years of education, multisite scanner differences, estimated total intracranial volume, and binarized cardiovascular disease risk.
Results:RM-ANCOVA revealed two-way group*time interactions such that those assigned cognitive training demonstrated greater improvement on proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures compared to their ET counterparts. Multiple linear regression showed higher baseline TLV associated with lower pre-post change on Processing Speed Training sub-composite (ß = -0.19, p = 0.04) but not other composite measures.
Conclusions:These findings demonstrate the utility of cognitive training for improving postintervention proximal performance in older adults. Additionally, pre-post proximal processing speed training change appear to be particularly sensitive to white matter hyperintensity load versus working memory training change. These data suggest that TLV may serve as an important factor for consideration when planning processing speed-based cognitive training interventions for remediation of cognitive decline in older adults.
1 Task-Based Functional Connectivity and Network Segregation of the Useful Field of View (UFOV) fMRI task
- Jessica N Kraft, Hanna K Hausman, Cheshire Hardcastle, Alejandro Albizu, Andrew O’Shea, Nicole D Evangelista, Emanuel M Boutzoukas, Emily J Van Etten, Pradyumna K Bharadwaj, Hyun Song, Samantha G Smith, Steven T DeKosky, Georg A Hishaw, Samuel Wu, Michael Marsiske, Ronald Cohen, Eric Porges, Adam J Woods
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 606-607
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Objective:
Interventions using a cognitive training paradigm called the Useful Field of View (UFOV) task have shown to be efficacious in slowing cognitive decline. However, no studies have looked at the engagement of functional networks during UFOV task completion. The current study aimed to (a) assess if regions activated during the UFOV fMRI task were functionally connected and related to task performance (henceforth called the UFOV network), (b) compare connectivity of the UFOV network to 7 resting-state functional connectivity networks in predicting proximal (UFOV) and near-transfer (Double Decision) performance, and (c) explore the impact of network segregation between higher-order networks and UFOV performance.
Participants and Methods:336 healthy older adults (mean age=71.6) completed the UFOV fMRI task in a Siemens 3T scanner. UFOV fMRI accuracy was calculated as the number of correct responses divided by 56 total trials. Double Decision performance was calculated as the average presentation time of correct responses in log ms, with lower scores equating to better processing speed. Structural and functional MRI images were processed using the default pre-processing pipeline within the CONN toolbox. The Artifact Rejection Toolbox was set at a motion threshold of 0.9mm and participants were excluded if more than 50% of volumes were flagged as outliers. To assess connectivity of regions associated with the UFOV task, we created 10 spherical regions of interest (ROIs) a priori using the WFU PickAtlas in SPM12. These include the bilateral pars triangularis, supplementary motor area, and inferior temporal gyri, as well as the left pars opercularis, left middle occipital gyrus, right precentral gyrus and right superior parietal lobule. We used a weighted ROI-to-ROI connectivity analysis to model task-based within-network functional connectivity of the UFOV network, and its relationship to UFOV accuracy. We then used weighted ROI-to-ROI connectivity analysis to compare the efficacy of the UFOV network versus 7 resting-state networks in predicting UFOV fMRI task performance and Double Decision performance. Finally, we calculated network segregation among higher order resting state networks to assess its relationship with UFOV accuracy. All functional connectivity analyses were corrected at a false discovery threshold (FDR) at p<0.05.
Results:ROI-to-ROI analysis showed significant within-network functional connectivity among the 10 a priori ROIs (UFOV network) during task completion (all pFDR<.05). After controlling for covariates, greater within-network connectivity of the UFOV network associated with better UFOV fMRI performance (pFDR=.008). Regarding the 7 resting-state networks, greater within-network connectivity of the CON (pFDR<.001) and FPCN (pFDR=. 014) were associated with higher accuracy on the UFOV fMRI task. Furthermore, greater within-network connectivity of only the UFOV network associated with performance on the Double Decision task (pFDR=.034). Finally, we assessed the relationship between higher-order network segregation and UFOV accuracy. After controlling for covariates, no significant relationships between network segregation and UFOV performance remained (all p-uncorrected>0.05).
Conclusions:To date, this is the first study to assess task-based functional connectivity during completion of the UFOV task. We observed that coherence within 10 a priori ROIs significantly predicted UFOV performance. Additionally, enhanced within-network connectivity of the UFOV network predicted better performance on the Double Decision task, while conventional resting-state networks did not. These findings provide potential targets to optimize efficacy of UFOV interventions.
78 BVMT-R Learning Ratio Moderates Cognitive Training Gains in Useful Field of View Task in Healthy Older Adults
- Cheshire Hardcastle, Jessica N. Kraft, Hanna K. Hausman, Andrew O’Shea, Alejandro Albizu, Nicole D. Evangelista, Emanuel Boutzoukas, Emily J. Van Etten, Pradyumna K. Bharadwaj, Hyun Song, Samantha G. Smith, Eric Porges, Steven DeKosky, Georg A. Hishaw, Samuel Wu, Michael Marsiske, Ronald Cohen, Gene E. Alexander, Adam J. Woods
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 180-181
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Objective:
Cognitive training using a visual speed-of-processing task, called the Useful Field of View (UFOV) task, reduced dementia risk and reduced decline in activities of daily living at a 10-year follow-up in older adults. However, there is variability in the level of cognitive gains after cognitive training across studies. One potential explanation for this variability could be moderating factors. Prior studies suggest variables moderating cognitive training gains share features of the training task. Learning trials of the Hopkins Verbal Learning Test-Revised (HVLT-R) and Brief Visuospatial Memory Test-Revised (BVMT-R) recruit similar cognitive abilities and have overlapping neural correlates with the UFOV task and speed-ofprocessing/working memory tasks and therefore could serve as potential moderators. Exploring moderating factors of cognitive training gains may boost the efficacy of interventions, improve rigor in the cognitive training literature, and eventually help provide tailored treatment recommendations. This study explored the association between the HVLT-R and BVMT-R learning and the UFOV task, and assessed the moderation of HVLT-R and BVMT-R learning on UFOV improvement after a 3-month speed-ofprocessing/attention and working memory cognitive training intervention in cognitively healthy older adults.
Participants and Methods:75 healthy older adults (M age = 71.11, SD = 4.61) were recruited as part of a larger clinical trial through the Universities of Florida and Arizona. Participants were randomized into a cognitive training (n=36) or education control (n=39) group and underwent a 40-hour, 12-week intervention. Cognitive training intervention consisted of practicing 4 attention/speed-of-processing (including the UFOV task) and 4 working memory tasks. Education control intervention consisted of watching 40-minute educational videos. The HVLT-R and BVMT-R were administered at the pre-intervention timepoint as part of a larger neurocognitive battery. The learning ratio was calculated as: trial 3 total - trial 1 total/12 - trial 1 total. UFOV performance was measured at pre- and post-intervention time points via the POSIT Brain HQ Double Decision Assessment. Multiple linear regressions predicted baseline Double Decision performance from HVLT-R and BVMT-R learning ratios controlling for study site, age, sex, and education. A repeated measures moderation analysis assessed the moderation of HVLT-R and BVMT-R learning ratio on Double Decision change from pre- to post-intervention for cognitive training and education control groups.
Results:Baseline Double Decision performance significantly associated with BVMT-R learning ratio (β=-.303, p=.008), but not HVLT-R learning ratio (β=-.142, p=.238). BVMT-R learning ratio moderated gains in Double Decision performance (p<.01); for each unit increase in BVMT-R learning ratio, there was a .6173 unit decrease in training gains. The HVLT-R learning ratio did not moderate gains in Double Decision performance (p>.05). There were no significant moderations in the education control group.
Conclusions:Better visuospatial learning was associated with faster Double Decision performance at baseline. Those with poorer visuospatial learning improved most on the Double Decision task after training, suggesting that healthy older adults who perform below expectations may show the greatest training gains. Future cognitive training research studying visual speed-of-processing interventions should account for differing levels of visuospatial learning at baseline, as this could impact the magnitude of training outcomes.
59 The Impact of Anxiety on Memory Performance in Older Adults with Depression
- Usha D. Persaud, Kevin J. Manning, Rong Wu, David C. Steffens
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 844-845
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Objective:
Late life depression (LLD) refers to a diagnosis of major depressive disorder in people older than 60, and has been linked to significant cognitive impairment and increased risk of Alzheimer's disease. Although anxiety and depression are highly comorbid, the impact of anxiety on cognition in LLD is far less researched. This is important given that over 20% of middle aged and older adults endorse clinically significant chronic worry. Generalized anxiety disorder in older adults with major depression is associated with poorer cognition and worse treatment outcomes compared with those without anxiety. Therefore, the purpose of the study is to examine the role of anxiety on memory in LLD. We hypothesized that presence of anxiety among older depressed adults would be associated with worse cognitive performance over time.
Participants and Methods:Participants included 124 individuals (69.4% female, 90.3% Caucasian) aged 60 or above (M = 71.5, SD = 7.4) who met criteria for major depression, single episode or recurrent. They completed the State Trait Anxiety Inventory, Montgomery Asberg Depression Rating Scale, and a measure of verbal episodic memory (WMS-IV Logical Memory) as part of a larger neuropsychological battery. Data were collected from baseline to three years as part of a larger NIMH-supported longitudinal study. Two-level linear mixed-effect models were fitted to predict memory. State and trait anxiety were used as time-varying predictors. The between-person (level 2) and within-person (level 1) effects of anxiety on memory were assessed controlling for the time trend, age, education, gender, race, and change in depression over time.
Results:Plot trajectories across variables revealed a negative correlation such that as anxiety decreased, memory improved over time. Hierarchical linear mixed-effect models revealed that average state anxiety was a marginally significant between-person (level2) predictor for memory [B=-0.041, t(128)=-1.8, p=0.083]. Individuals with greater average state anxiety were more likely to experience memory decline compared to those with lower average state anxiety. In addition, the within-person effect (level 1) of state anxiety was significant [B=-0.096, t(253)=-2.7, p=0.007]. As an individual's anxiety increased over time, their memory declined. Trait anxiety showed a significant within-person effect on memory [B=-0.087, t(254)=-2.0, p=0.048], but a non-significant between-person effect [B=-0.005, t(124)=-0.06, p=0.95].
Conclusions:Anxiety appears to increase the risk of memory decline in older adults with major depression, a cohort who are already at risk of cognitive decline. Changes in anxiety increased risk of memory decline even when accounting for changes in depression over time. Although the causal link between anxiety and cognitive impairment remains unclear, it is possible that anxiety and worry may compete for cognitive resources necessary for demanding tasks and situations, detracting from abilities, such as attention and working memory. Older adults with depression may also have difficulty coping adaptively with anxiety, which may negatively affect cognition. Finally, presence of anxiety may represent a form of mild behavioral impairment, a prodrome of cognitive decline leading to dementia. Overall, the present study highlights the negative impact of anxiety on memory performance, indicating that treatment interventions targeting anxiety in older adults are essential to help prevent cognitive decline.
6 Adjunctive Transcranial Direct Current Stimulation and Cognitive Training Alters Default Mode and Frontoparietal Control Network Connectivity in Older Adults
- Hanna K Hausman, Jessica N Kraft, Cheshire Hardcastle, Nicole D Evangelista, Emanuel M Boutzoukas, Andrew O’Shea, Alejandro Albizu, Emily J Van Etten, Pradyumna K Bharadwaj, Hyun Song, Samantha G Smith, Eric S Porges, Georg A Hishaw, Samuel Wu, Steven DeKosky, Gene E Alexander, Michael Marsiske, Ronald A Cohen, Adam J Woods
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 675-676
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Objective:
Aging is associated with disruptions in functional connectivity within the default mode (DMN), frontoparietal control (FPCN), and cingulo-opercular (CON) resting-state networks. Greater within-network connectivity predicts better cognitive performance in older adults. Therefore, strengthening network connectivity, through targeted intervention strategies, may help prevent age-related cognitive decline or progression to dementia. Small studies have demonstrated synergistic effects of combining transcranial direct current stimulation (tDCS) and cognitive training (CT) on strengthening network connectivity; however, this association has yet to be rigorously tested on a large scale. The current study leverages longitudinal data from the first-ever Phase III clinical trial for tDCS to examine the efficacy of an adjunctive tDCS and CT intervention on modulating network connectivity in older adults.
Participants and Methods:This sample included 209 older adults (mean age = 71.6) from the Augmenting Cognitive Training in Older Adults multisite trial. Participants completed 40 hours of CT over 12 weeks, which included 8 attention, processing speed, and working memory tasks. Participants were randomized into active or sham stimulation groups, and tDCS was administered during CT daily for two weeks then weekly for 10 weeks. For both stimulation groups, two electrodes in saline-soaked 5x7 cm2 sponges were placed at F3 (cathode) and F4 (anode) using the 10-20 measurement system. The active group received 2mA of current for 20 minutes. The sham group received 2mA for 30 seconds, then no current for the remaining 20 minutes.
Participants underwent resting-state fMRI at baseline and post-intervention. CONN toolbox was used to preprocess imaging data and conduct region of interest (ROI-ROI) connectivity analyses. The Artifact Detection Toolbox, using intermediate settings, identified outlier volumes. Two participants were excluded for having greater than 50% of volumes flagged as outliers. ROI-ROI analyses modeled the interaction between tDCS group (active versus sham) and occasion (baseline connectivity versus postintervention connectivity) for the DMN, FPCN, and CON controlling for age, sex, education, site, and adherence.
Results:Compared to sham, the active group demonstrated ROI-ROI increases in functional connectivity within the DMN following intervention (left temporal to right temporal [T(202) = 2.78, pFDR < 0.05] and left temporal to right dorsal medial prefrontal cortex [T(202) = 2.74, pFDR < 0.05]. In contrast, compared to sham, the active group demonstrated ROI-ROI decreases in functional connectivity within the FPCN following intervention (left dorsal prefrontal cortex to left temporal [T(202) = -2.96, pFDR < 0.05] and left dorsal prefrontal cortex to left lateral prefrontal cortex [T(202) = -2.77, pFDR < 0.05]). There were no significant interactions detected for CON regions.
Conclusions:These findings (a) demonstrate the feasibility of modulating network connectivity using tDCS and CT and (b) provide important information regarding the pattern of connectivity changes occurring at these intervention parameters in older adults. Importantly, the active stimulation group showed increases in connectivity within the DMN (a network particularly vulnerable to aging and implicated in Alzheimer’s disease) but decreases in connectivity between left frontal and temporal FPCN regions. Future analyses from this trial will evaluate the association between these changes in connectivity and cognitive performance post-intervention and at a one-year timepoint.
9 Connecting memory and functional brain networks in older adults: a resting state fMRI study
- Jori L Waner, Hanna K Hausman, Jessica N Kraft, Cheshire Hardcastle, Nicole D Evangelista, Andrew O’Shea, Alejandro Albizu, Emanuel M Boutzoukas, Emily J Van Etten, Pradyumna K Bharadwaj, Hyun Song, Samantha G Smith, Steven T DeKosky, Georg A Hishaw, Samuel S Wu, Michael Marsiske, Ronald Cohen, Gene E Alexander, Eric C Porges, Adam J Woods
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 527-528
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Objective:
Nonpathological aging has been linked to decline in both verbal and visuospatial memory abilities in older adults. Disruptions in resting-state functional connectivity within well-characterized, higherorder cognitive brain networks have also been coupled with poorer memory functioning in healthy older adults and in older adults with dementia. However, there is a paucity of research on the association between higherorder functional connectivity and verbal and visuospatial memory performance in the older adult population. The current study examines the association between resting-state functional connectivity within the cingulo-opercular network (CON), frontoparietal control network (FPCN), and default mode network (DMN) and verbal and visuospatial learning and memory in a large sample of healthy older adults. We hypothesized that greater within-network CON and FPCN functional connectivity would be associated with better immediate verbal and visuospatial memory recall. Additionally, we predicted that within-network DMN functional connectivity would be associated with improvements in delayed verbal and visuospatial memory recall. This study helps to glean insight into whether within-network CON, FPCN, or DMN functional connectivity is associated with verbal and visuospatial memory abilities in later life.
Participants and Methods:330 healthy older adults between 65 and 89 years old (mean age = 71.6 ± 5.2) were recruited at the University of Florida (n = 222) and the University of Arizona (n = 108). Participants underwent resting-state fMRI and completed verbal memory (Hopkins Verbal Learning Test - Revised [HVLT-R]) and visuospatial memory (Brief Visuospatial Memory Test - Revised [BVMT-R]) measures. Immediate (total) and delayed recall scores on the HVLT-R and BVMT-R were calculated using each test manual’s scoring criteria. Learning ratios on the HVLT-R and BVMT-R were quantified by dividing the number of stimuli (verbal or visuospatial) learned between the first and third trials by the number of stimuli not recalled after the first learning trial. CONN Toolbox was used to extract average within-network connectivity values for CON, FPCN, and DMN. Hierarchical regressions were conducted, controlling for sex, race, ethnicity, years of education, number of invalid scans, and scanner site.
Results:Greater CON connectivity was significantly associated with better HVLT-R immediate (total) recall (ß = 0.16, p = 0.01), HVLT-R learning ratio (ß = 0.16, p = 0.01), BVMT-R immediate (total) recall (ß = 0.14, p = 0.02), and BVMT-R delayed recall performance (ß = 0.15, p = 0.01). Greater FPCN connectivity was associated with better BVMT-R learning ratio (ß = 0.13, p = 0.04). HVLT-R delayed recall performance was not associated with connectivity in any network, and DMN connectivity was not significantly related to any measure.
Conclusions:Connectivity within CON demonstrated a robust relationship with different components of memory function as well across verbal and visuospatial domains. In contrast, FPCN only evidenced a relationship with visuospatial learning, and DMN was not significantly associated with memory measures. These data suggest that CON may be a valuable target in longitudinal studies of age-related memory changes, but also a possible target in future non-invasive interventions to attenuate memory decline in older adults.
Inertial wave attractors in librating cuboids
- Ke Wu, Bruno D. Welfert, Juan M. Lopez
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- Journal:
- Journal of Fluid Mechanics / Volume 973 / 25 October 2023
- Published online by Cambridge University Press:
- 17 October 2023, A20
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Perturbed rapidly rotating flows are dominated by inertial oscillations, with restricted group velocity directions, due to the restorative nature of the Coriolis force. In containers with some boundaries oblique to the rotation axis, the inertial oscillations may focus upon reflections, whereby their energy increases whilst their wavelength decreases and their trajectories focus onto attractor regions. In a linear inviscid setting, these attractors are Delta-like distributions. The linear inviscid setting is obtained formally by setting both Ekman number ${E}$ (ratio of inertial to viscous time scales) and Rossby number ${Ro}$ (non-dimensional amplitude of the forcing that drives the inertial oscillations) to zero. These settings raise fundamental questions, in particular concerning the nature of energy dissipation in the vanishing Ekman number regime. Here, we consider a simple container geometry, a rectangular cuboid, in which the direction of the rotation axis is oblique to four of its walls, subject to librational forcing (small-amplitude harmonic oscillations of the rotation rate). This geometry allows for accurate and efficient direct numerical simulations of the three-dimensional incompressible Navier–Stokes equations with no-slip boundary conditions using a spectral-Galerkin spatial discretisation along with a third-order temporal discretisation. Solutions with Ekman and Rossby numbers as small as ${E}={Ro}=10^{-8}$ reveal many details of how the inertial oscillations focus, at the libration frequency considered, onto attractors, and how the focusing leads to increased localised nonlinear and dissipative processes as ${E}$ and ${Ro}$ are reduced. Even for extremely small forcing amplitudes, nonlinear effects have important dynamic consequences for the attractors.
Trajectories of remitted psychotic depression: identification of predictors of worsening by machine learning
- Samprit Banerjee, Yiyuan Wu, Kathleen S. Bingham, Patricia Marino, Barnett S. Meyers, Benoit H. Mulsant, Nicholas H. Neufeld, Lindsay D. Oliver, Jonathan D. Power, Anthony J. Rothschild, Jo Anne Sirey, Aristotle N. Voineskos, Ellen M. Whyte, George S. Alexopoulos, Alastair J. Flint
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- Psychological Medicine / Volume 54 / Issue 6 / April 2024
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- 11 October 2023, pp. 1142-1151
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Background
Remitted psychotic depression (MDDPsy) has heterogeneity of outcome. The study's aims were to identify subgroups of persons with remitted MDDPsy with distinct trajectories of depression severity during continuation treatment and to detect predictors of membership to the worsening trajectory.
MethodOne hundred and twenty-six persons aged 18–85 years participated in a 36-week randomized placebo-controlled trial (RCT) that examined the clinical effects of continuing olanzapine once an episode of MDDPsy had remitted with sertraline plus olanzapine. Latent class mixed modeling was used to identify subgroups of participants with distinct trajectories of depression severity during the RCT. Machine learning was used to predict membership to the trajectories based on participant pre-trajectory characteristics.
ResultsSeventy-one (56.3%) participants belonged to a subgroup with a stable trajectory of depression scores and 55 (43.7%) belonged to a subgroup with a worsening trajectory. A random forest model with high prediction accuracy (AUC of 0.812) found that the strongest predictors of membership to the worsening subgroup were residual depression symptoms at onset of remission, followed by anxiety score at RCT baseline and age of onset of the first lifetime depressive episode. In a logistic regression model that examined depression score at onset of remission as the only predictor variable, the AUC (0.778) was close to that of the machine learning model.
ConclusionsResidual depression at onset of remission has high accuracy in predicting membership to worsening outcome of remitted MDDPsy. Research is needed to determine how best to optimize the outcome of psychotic MDDPsy with residual symptoms.
An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges
- Karamarie Fecho, Chris Bizon, Tursynay Issabekova, Sierra Moxon, Anne E. Thessen, Shervin Abdollahi, Sergio E. Baranzini, Basazin Belhu, William E. Byrd, Lawrence Chung, Andrew Crouse, Marc P. Duby, Stephen Ferguson, Aleksandra Foksinska, Laura Forero, Jennifer Friedman, Vicki Gardner, Gwênlyn Glusman, Jennifer Hadlock, Kristina Hanspers, Eugene Hinderer, Charlotte Hobbs, Gregory Hyde, Sui Huang, David Koslicki, Philip Mease, Sandrine Muller, Christopher J. Mungall, Stephen A. Ramsey, Jared Roach, Irit Rubin, Shepherd H. Schurman, Anath Shalev, Brett Smith, Karthik Soman, Sarah Stemann, Andrew I. Su, Casey Ta, Paul B. Watkins, Mark D. Williams, Chunlei Wu, Colleen H. Xu, The Biomedical Data Translator Consortium
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- Journal of Clinical and Translational Science / Volume 7 / Issue 1 / 2023
- Published online by Cambridge University Press:
- 14 September 2023, e214
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Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph–based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly “Question-of-the-Month (QotM) Challenge” series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.
Penn Healthy Diet survey: pilot validation and scoring
- Charlene W. Compher, Ryan Quinn, Richard Haslam, Elizabeth Bader, Joellen Weaver, Scott Dudek, Marylyn D. Ritchie, James D. Lewis, Gary D. Wu
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- British Journal of Nutrition / Volume 131 / Issue 1 / 14 January 2024
- Published online by Cambridge University Press:
- 31 July 2023, pp. 156-162
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- 14 January 2024
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Though diet quality is widely recognised as linked to risk of chronic disease, health systems have been challenged to find a user-friendly, efficient way to obtain information about diet. The Penn Healthy Diet (PHD) survey was designed to fill this void. The purposes of this pilot project were to assess the patient experience with the PHD, to validate the accuracy of the PHD against related items in a diet recall and to explore scoring algorithms with relationship to the Healthy Eating Index (HEI)-2015 computed from the recall data. A convenience sample of participants in the Penn Health BioBank was surveyed with the PHD, the Automated Self-Administered 24-hour recall (ASA24) and experience questions. Kappa scores and Spearman correlations were used to compare related questions in the PHD to the ASA24. Numerical scoring, regression tree and weighted regressions were computed for scoring. Participants assessed the PHD as easy to use and were willing to repeat the survey at least annually. The three scoring algorithms were strongly associated with HEI-2015 scores using National Health and Nutrition Examination Survey 2017–2018 data from which the PHD was developed and moderately associated with the pilot replication data. The PHD is acceptable to participants and at least moderately correlated with the HEI-2015. Further validation in a larger sample will enable the selection of the strongest scoring approach.
Preterm birth associated alterations in brain structure, cognitive functioning and behavior in children from the ABCD dataset
- Weibin Ji, Guanya Li, Fukun Jiang, Yaqi Zhang, Feifei Wu, Wenchao Zhang, Yang Hu, Jia Wang, Xiaorong Wei, Yuefeng Li, Peter Manza, Dardo Tomasi, Xinbo Gao, Gene-Jack Wang, Yi Zhang, Nora D Volkow
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- Psychological Medicine / Volume 54 / Issue 2 / January 2024
- Published online by Cambridge University Press:
- 27 June 2023, pp. 409-418
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Background
Preterm birth is a global health problem and associated with increased risk of long-term developmental impairments, but findings on the adverse outcomes of prematurity have been inconsistent.
MethodsData were obtained from the baseline session of the ongoing longitudinal Adolescent Brain and Cognitive Development (ABCD) Study. We identified 1706 preterm children and 1865 matched individuals as Control group and compared brain structure (MRI data), cognitive function and mental health symptoms.
ResultsResults showed that preterm children had higher psychopathological risk and lower cognitive function scores compared to controls. Structural MRI analysis indicated that preterm children had higher cortical thickness in the medial orbitofrontal cortex, parahippocampal gyrus, temporal and occipital gyrus; smaller volumes in the temporal and parietal gyrus, cerebellum, insula and thalamus; and smaller fiber tract volumes in the fornix and parahippocampal-cingulum bundle. Partial correlation analyses showed that gestational age and birth weight were associated with ADHD symptoms, picvocab, flanker, reading, fluid cognition composite, crystallized cognition composite and total cognition composite scores, and measures of brain structure in regions involved with emotional regulation, attention and cognition.
ConclusionsThese findings suggest a complex interplay between psychopathological risk and cognitive deficits in preterm children that is associated with changes in regional brain volumes, cortical thickness, and structural connectivity among cortical and limbic brain regions critical for cognition and emotional well-being.
360 Waste not, test more: Innovations in tissue processing to expand the testing of clinical specimens
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- Wilfrido Mojica, Bei Yang, Chang Chieh Hsu, Yun Wu, Alexandra Izydorczak, Troy D. Wood, Dara Cho, Natesh Parashurama, Donald Yergeau, Supriya D Mahajan
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- Journal of Clinical and Translational Science / Volume 7 / Issue s1 / April 2023
- Published online by Cambridge University Press:
- 24 April 2023, pp. 106-107
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OBJECTIVES/GOALS: Clinical tissue specimens are primarily destined for formalin fixed, paraffin embedded processing to create a basis for diagnosis by microscopic examination. Innovations in specimen processing are required to expand its availability for inclusion as the substrate in assays that can contribute to the further development of Precision Medicine. METHODS/STUDY POPULATION: Transurethral resection of bladder tumors were selected for testing based on availability and tissue composition. A wash step was used to generate daughter aliquots composed of dislodged cells and a solution with prior contact to the parent tissue. This wash step served two purposes: 1) reduce the amount of contaminating material from spreading to other cases, a problem known to be associated with this type of specimen; and 2) create aliquots from which additional informative data could be generated. These daughter aliquots were then examined to determine their value as a source for exosome profiling, metabolomic studies, molecular characterization and organoid development. The parent tissue was not compromised, was able to undergo conventional processing and yielded results equivalent to unwashed specimens. RESULTS/ANTICIPATED RESULTS: Exosomes secreted by the tumor cells were identified to be present in the daughter aliquots by a combination of their isolation using CD31 and detection of miR-21 expression. These exosomes were confirmed to be not related to fragmented cells from testing for beta-tubulin. A global/discovery-based approach using mass spectrometry provided insights into early characterization of metabolomic profiles present in these tumor cells. Ample amounts of high quality DNA (226 ng/ul concentrations; 11.3 ug total) were recovered from the dislodged, excess cells in the wash for molecular studies. Finally, from viable cells recovered in one of the daughter wash aliquots, the ability to grow organoids was proven to be possible and reproducible. DISCUSSION/SIGNIFICANCE: Based on these results, the value of the clinical specimen can be markedly expanded for utilization in research and possible clinical use without detracting from the parent tissue. This non-destructive, easy to adopt wash procedure can potentially lead to an influx of data that may ultimately prove useful in improving patient care.
Attitudes of Taiwan veterinarians towards animal welfare
- S-Y Wu, Y-T Lai, C-Y Fei, D-S Jong
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- Animal Welfare / Volume 24 / Issue 2 / May 2015
- Published online by Cambridge University Press:
- 01 January 2023, pp. 223-228
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A survey was carried out to examine the attitudes of veterinarians in Taiwan towards animal welfare issues and current systems related to animal protection. The respondents were asked to express the extent to which they agreed with the importance of the Five Freedoms and relevant education in animal welfare. The survey was sent to 889 veterinarians and the response rate was 34%. According to the findings, veterinarians in Taiwan consider that current animal protection laws in Taiwan, and their relevant systems, are unable to protect animals effectively. They mostly have an uncertain attitude towards the statement that animal welfare can upgrade their professional abilities or enhance their image, in that they have a relative lack of awareness of animal welfare as well as also lacking further understanding of the importance and influence of animal welfare. However, many veterinarians strongly support the content of ‘The Five Freedoms’ and relevant training of animal welfare and ethics. Instead of denying the necessity and importance of the relevant issues, we consider that some veterinarians lack confidence in animal welfare merely because of a lack of relevant training. The results of the survey indicate that providing veterinarians with professional education of animal welfare is the first step which brooks no delay.
Boundary-confined waves in a librating cube
- Juan M. Lopez, Jie Shen, Bruno D. Welfert, Ke Wu
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- Journal of Fluid Mechanics / Volume 952 / 10 December 2022
- Published online by Cambridge University Press:
- 28 November 2022, R2
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When a fluid-filled cube rotating rapidly about an axis passing through two opposite vertices is subjected to harmonic modulations of its rotation rate (librations) at a modulation frequency that is $2/\sqrt {3}$ times the mean rotation frequency, all walls of the cube have critical reflection slopes. As such, all inertial wave beams emitted from edges and vertices of the cube in response to the librations are trapped in thin oscillatory boundary layers for forcing amplitudes (Rossby numbers) below a critical value which depends on the Ekman number (ratio of rotation to viscous time scales). How the resulting oscillatory boundary layer flow, referred to as a boundary-confined wave, depends on Ekman and Rossby numbers is examined in detail over several decades. Of particular interest is how the mean flow grows with increasing forcing amplitude, leading to instability resulting from nonlinear interactions between the mean flow and waves in the oscillatory boundary layers, injecting intense small-scale structures throughout the cube.
Using machine learning with intensive longitudinal data to predict depression and suicidal ideation among medical interns over time
- Adam G. Horwitz, Shane D. Kentopp, Jennifer Cleary, Katherine Ross, Zhenke Wu, Srijan Sen, Ewa K. Czyz
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- Psychological Medicine / Volume 53 / Issue 12 / September 2023
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- 30 September 2022, pp. 5778-5785
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Background
Use of intensive longitudinal methods (e.g. ecological momentary assessment, passive sensing) and machine learning (ML) models to predict risk for depression and suicide has increased in recent years. However, these studies often vary considerably in length, ML methods used, and sources of data. The present study examined predictive accuracy for depression and suicidal ideation (SI) as a function of time, comparing different combinations of ML methods and data sources.
MethodsParticipants were 2459 first-year training physicians (55.1% female; 52.5% White) who were provided with Fitbit wearable devices and assessed daily for mood. Linear [elastic net regression (ENR)] and non-linear (random forest) ML algorithms were used to predict depression and SI at the first-quarter follow-up assessment, using two sets of variables (daily mood features only, daily mood features + passive-sensing features). To assess accuracy over time, models were estimated iteratively for each of the first 92 days of internship, using data available up to that point in time.
ResultsENRs using only the daily mood features generally had the best accuracy for predicting mental health outcomes, and predictive accuracy within 1 standard error of the full 92 day models was attained by weeks 7–8. Depression at 92 days could be predicted accurately (area under the curve >0.70) after only 14 days of data collection.
ConclusionsSimpler ML methods may outperform more complex methods until passive-sensing features become better specified. For intensive longitudinal studies, there may be limited predictive value in collecting data for more than 2 months.