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Colorectal cancer is the third most commonly diagnosed cancer in the world that affects both men and women. Approximately 40% of colorectal cancer patients exhibit cognitive impairment in executive functions including verbal learning, verbal memory, and information processing that is independent of chemotherapy. However, little information is currently available regarding the neural mechanisms underlying colorectal cancer-related cognitive decline (CRCD). In this study, we utilized highly sensitive 7 Tesla magnetic resonance imaging methods combined with standardized cognitive assessments to investigate the changes in brain local functional connectivity in early-stage colorectal cancer survivors compared to healthy controls. We observed that early-stage colorectal cancer survivors exhibited increased regional homogeneity (ReHo) in the left hippocampus, parahippocampal gyrus, and inferior temporal gyrus, along with decreased ReHo in the left inferior frontal gyrus, which were associated with reduced verbal memory performance compared to healthy controls. Furthermore, survivors exhibited significantly weaker inter-regional functional connectivity, suggesting a potential disruption in coordination among regions critical for verbal memory. Collectively, these findings indicate a maladaptive mechanism in the medial temporal lobes that is associated with declines in verbal memory processes among colorectal cancer survivors. ReHo analysis was found to be a valuable tool for characterizing the neurophysiological basis of colorectal CRCD and presents the medial temporal lobe as a promising target for therapeutic interventions.

Background Subjective cognitive decline (SCD) is one of the earliest noticeable symptoms of AD and is defined as having self‐perceived worsening of cognition without exhibiting objective impairments on standardized clinical cognitive tests (PMID: 31958406). Since not all individuals with SCD will convert into MCI or AD, it is important to accurately characterize and model the subtle changes in SCD brains that may be predictive of future trajectory towards AD. Method Longitudinal MRI data and AD Assessment Scale (ADAS‐Cog) scores from 70 subjects with SCD and 100 healthy controls (HC) were acquired from the ADNI 2 and 3 database. Standard resting‐state fMRI pre‐processing and calculations of 3D regional homogeneity (ReHo) based on 27 neighboring voxels was performed using Data Processing & Analysis for Brain Imaging (DPABI) while site effects were minimized via CovBat harmonization (PMID: 37086875). Within a gray matter mask, two sample t‐tests were performed between the HC and SCD groups' ReHo maps using FSL's randomization procedure with 5000 permutations where age, sex, head motion, and voxel‐wise GM volume were included as covariates. Significance levels were adjusted for multiple comparisons using threshold‐free cluster enhancement correction. An ordinary least squares regression (OLS) model was developed for predicting future ADAS‐Cog scores based on baseline (year 0) clinical scores and ReHo values. Result At baseline compared to HC, SCD revealed significant ReHo decreases in the frontal and occipital regions along with significant increases in the temporal regions (Table 1). Correlation maps of SCD ReHo and ADAS‐Cog scores indicated negative correlations in the bilateral insula and temporal regions along with positive correlations in the medial parietal regions (Figure 1). The OLS model developed from these features and baseline clinical scores was able to predict ADAS‐Cog scores at year 4 with a goodness‐of‐fit (r2) of 0.72 among a randomized 50:50 training and test set. Independently, the model's r2 based on baseline clinical scores alone was 0.64. Conclusion ReHo reflects neural synchronization within localized regions, providing insights into brain network coherence. Individuals with SCD exhibit significantly different resting‐state ReHo features compared to HCs. With predictive modeling, these ReHo features can help augment the long‐term projection of early AD trajectories.

Subjective cognitive decline (SCD) is one of the earliest noticeable symptoms of AD and is defined as having self-perceived worsening of cognition without exhibiting objective impairments on standardized clinical cognitive tests (PMID: 31958406). Since not all individuals with SCD will convert into MCI or AD, it is important to accurately characterize and model the subtle changes in SCD brains that may be predictive of future trajectory towards AD. Longitudinal MRI data and AD Assessment Scale (ADAS-Cog) scores from 70 subjects with SCD and 100 healthy controls (HC) were acquired from the ADNI 2 and 3 database. Standard resting-state fMRI pre-processing and calculations of 3D regional homogeneity (ReHo) based on 27 neighboring voxels was performed using Data Processing & Analysis for Brain Imaging (DPABI) while site effects were minimized via CovBat harmonization (PMID: 37086875). Within a gray matter mask, two sample t-tests were performed between the HC and SCD groups' ReHo maps using FSL's randomization procedure with 5000 permutations where age, sex, head motion, and voxel-wise GM volume were included as covariates. Significance levels were adjusted for multiple comparisons using threshold-free cluster enhancement correction. An ordinary least squares regression (OLS) model was developed for predicting future ADAS-Cog scores based on baseline (year 0) clinical scores and ReHo values. At baseline compared to HC, SCD revealed significant ReHo decreases in the frontal and occipital regions along with significant increases in the temporal regions (Table 1). Correlation maps of SCD ReHo and ADAS-Cog scores indicated negative correlations in the bilateral insula and temporal regions along with positive correlations in the medial parietal regions (Figure 1). The OLS model developed from these features and baseline clinical scores was able to predict ADAS-Cog scores at year 4 with a goodness-of-fit (r ) of 0.72 among a randomized 50:50 training and test set. Independently, the model's r based on baseline clinical scores alone was 0.64. ReHo reflects neural synchronization within localized regions, providing insights into brain network coherence. Individuals with SCD exhibit significantly different resting-state ReHo features compared to HCs. With predictive modeling, these ReHo features can help augment the long-term projection of early AD trajectories.

The Contingency Naming Test (CNT; Taylor et al, 1987) is a measure initially designed to assess aspects of executive functioning, such as processing speed and response inhibition, in children. The measure has shown initial utility in identifying differences in executive function among adult clinical groups; however, there is an absence of adequate normative data for use with adults. The current set of studies expanded normative data upward for use with young adult samples and provided further data on the construct validity of the CNT in three adult samples. Study 1 provided normative data for a healthy college student sample that completed a neuropsychological battery. Performances showed continued improvement above child norms, consistent with theories of executive function development. Exploratory factor analysis showed that the CNT is most closely related to measures of processing speed, as well as elements of response inhibition within the latter trials. Study 2 utilized a clinical sample of young adults with ADHD/LD, psychological diagnoses, or no diagnosis. Performance on the CNT was significantly worse for the ADHD/LD group on the latter inhibition and switching trials, suggesting clinical utility for the instrument. Study 3 focused on potential use of the CNT with older adults. The CNT was administered to a sample of community-dwelling older adults as part of a memory assessment battery. Results showed the expected developmental pattern, with notable age-related decline in performance. Overall, results from this set of studies provide added support for the utility of the CNT as a measure of executive abilities. However, more research is needed to determine patterns of performance among other clinical groups, as well as to better understand how performance patterns may change in interim age ranges, such as middle age.

Background Hematopoietic stem cell transplantation (HSCT) is a common therapy for many hematologic malignancies. While advances in transplant practice have improved cancer-specific outcomes, multiple and debilitating long term physical and psychologic effects remain. Patients undergoing allogeneic bone marrow transplantation (allo-BMT) are often critically ill at initial diagnosis and with necessary sequential treatments become increasingly frail and deconditioned. Despite modern treatment regimens and support, cardiovascular disease remains a leading cause of non-relapse mortality among allo-BMT survivors. Well-established multi-disciplinary care models such as cardiac rehabilitation offer holistic care including exercise training, nursing support, physical/occupational therapy, psychosocial support and nutritional education. HSCT patients may be excluded from conventional outpatient physical rehabilitation programs due to prolonged pancytopenia and frequent hospital admissions. In Canada, dedicated cancer-specific rehabilitation programs are available only at major tertiary academic centers. Methods The primary aim of this study will evaluate the feasibility and acceptability of a multimodal care navigation (nursing, exercise, nutrition) intervention with content delivery facilitated by a supportive care web-based ‘app’ extending from diagnosis to 1 year in the allogeneic bone marrow transplant population. Adult patients scheduled for allo-BMT will receive support from exercise specialist, nursing support and dietician expertise alongside a supportive care ‘app’ with additional in-person or virtual cardiac rehabilitation support. Discussion To our knowledge, no research team is taking such a holistic, multidisciplinary approach to address the debilitating physiologic and psychological consequences of allo-BMT. We expect the findings to inform the optimal timing and patient preferences to develop studies examining risk-specific, individualized interventions (including exercise, pharmacotherapy, combination treatments) to reduce or prevent symptoms and dysfunction. We expect this innovative program to identify ways to benefit innumerable patients with hematologic and other malignancies. Ultimately, we hope to transform supportive care in hematopoietic stem cell transplantation. Trial Registration Clinicaltrials.gov ID: NCT05579678.

Using a novel trait-based measure, we examined genetic variants associated with obsessive-compulsive (OC) traits and tested whether OC traits and obsessive-compulsive disorder (OCD) shared genetic risk. We conducted a genome-wide association analysis (GWAS) of OC traits using the Toronto Obsessive-Compulsive Scale (TOCS) in 5018 unrelated Caucasian children and adolescents from the community (Spit for Science sample). We tested the hypothesis that genetic variants associated with OC traits from the community would be associated with clinical OCD using a meta-analysis of all currently available OCD cases. Shared genetic risk was examined between OC traits and OCD in the respective samples using polygenic risk score and genetic correlation analyses. A locus tagged by rs7856850 in an intron of PTPRD (protein tyrosine phosphatase δ) was significantly associated with OC traits at the genome-wide significance level (p = 2.48 × 10−8). rs7856850 was also associated with OCD in a meta-analysis of OCD case/control genome-wide datasets (p = 0.0069). The direction of effect was the same as in the community sample. Polygenic risk scores from OC traits were significantly associated with OCD in case/control datasets and vice versa (p’s < 0.01). OC traits were highly, but not significantly, genetically correlated with OCD (rg = 0.71, p = 0.062). We report the first validated genome-wide significant variant for OC traits in PTPRD, downstream of the most significant locus in a previous OCD GWAS. OC traits measured in the community sample shared genetic risk with OCD case/control status. Our results demonstrate the feasibility and power of using trait-based approaches in community samples for genetic discovery.

Over the past several years, scholars of political behavior have become increasingly interested in the nationalization of U.S. elections. Research has shown that there is now a strong connection between presidential vote patterns and voting in House, Senate, gubernatorial, and state legislative elections. In this article, we extend previous research by examining the role of the presidential vote in state supreme court elections. Using an original dataset containing county-level election results (N = 15,237) from 2000-2018 for all states that hold partisan or nonpartisan state supreme court elections, we examine the influence of presidential vote share in state supreme court elections. A number of important findings emerge. First, we find that presidential vote share influences voting in state supreme court contests. There is a statistically significant relationship in both partisan and nonpartisan elections even after controlling for incumbency, though the relationship is much stronger in states with partisan elections. Second, the relationship between presidential vote share and the state supreme court vote has been quite stable over time in states with partisan elections. Third, in states with states with nonpartisan elections, there has been some variability in the relationship between presidential and state supreme court voting patterns, although the data reveal an uptick in the strength of the relationship over time. Future research should continue to track the role of national political forces in state supreme court elections.