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In August 2012, a Lasiurus cinereus (Hoary Bat) and 2 Lasiurus borealis (Eastern Red Bat) were netted near Donkin, Cape Breton Island, NS, Canada. Acoustic studies showed the presence of Hoary Bats on at least 3 nights and Eastern Red Bats on at least 16 nights, over a 32-night-long survey starting on 21 August 2012. These records are the first for both species on Cape Breton Island, and significantly extend the known distribution of Eastern Red Bats.

In August 2012, a Lasiurus cinereus (Hoary Bat) and 2 Lasiurus borealis (Eastern Red Bat) were netted near Donkin, Cape Breton Island, NS, Canada. Acoustic studies showed the presence of Hoary Bats on at least 3 nights and Eastern Red Bats on at least 16 nights, over a 32-night-long survey starting on 21 August 2012. These records are the first for both species on Cape Breton Island, and significantly extend the known distribution of Eastern Red Bats.

Medial temporal lobe (MTL) atrophy measured on MRI is a sensitive biomarker of AD-linked neurodegeneration but is not specific to AD. LATE is a common AD co-pathology that is challenging to distinguish from AD based on available validated biomarkers. LATE and AD are both associated with hippocampus and entorhinal cortex atrophy, but recent studies suggest that there are differences in the severity and spatial patterns of atrophy. We sought to use postmortem MRI and histology to examine how MRI morphometric measures in AD and LATE relate to direct measures of neurodegeneration, including neuron number, size, and density. Thionin-stained 50µm histology sections from 24 brain donors (5 AD-LATE-, 14 AD+LATE-, 5 AD+LATE+) with available 9.4T postmortem MRI were used to delineate subfields CA1, subiculum and entorhinal cortex. Deep learning method StarDist was used to detect star-shaped objects in thionine slides, combined with weakly-supervised learning to identify artifact-free cortical regions and Gaussian mixture modeling to distinguish neurons from glia (Figure 1AB). Validation against stereology measures of neuronal/glial density was performed in 50 separate regions. Neuronal measures were compared to MTL volume and thickness measures extracted from MRI. Automated neuronal density estimates (r=0.72, Figure 1C) agreed with stereology, but not glial density. Estimated number and size of neurons in CA1 and ERC were higher in individuals with less CA1/ERC atrophy (Figure 2) consistent with greater neuronal loss in advanced AD and LATE. However, CA1 neuronal and glial density, and ERC glial density, were higher in individuals with greater atrophy, suggesting tighter packing of neurons in remaining tissue and significant contribution of neuropil loss to MRI-based atrophy measures. Pointwise analysis in Figure 3 shows patterns of association between regional MTL thickness and CA1 neuronal count, size, and density measures. These initial feasibility results in two sections in 24 brain donors encourage us to apply this pipeline to a larger dataset of paired postmortem MRI and serial histology sections (Ravikumar et al., 2024) and to study associations between tau pathology, neuronal loss, and MRI-based measures of atrophy, with the aim of better differentiating atrophy linked to LATE and AD.

Background Medial temporal lobe (MTL) atrophy measured on MRI is a sensitive biomarker of AD‐linked neurodegeneration but is not specific to AD. LATE is a common AD co‐pathology that is challenging to distinguish from AD based on available validated biomarkers. LATE and AD are both associated with hippocampus and entorhinal cortex atrophy, but recent studies suggest that there are differences in the severity and spatial patterns of atrophy. We sought to use postmortem MRI and histology to examine how MRI morphometric measures in AD and LATE relate to direct measures of neurodegeneration, including neuron number, size, and density. Method Thionin‐stained 50µm histology sections from 24 brain donors (5 AD‐LATE‐, 14 AD+LATE‐, 5 AD+LATE+) with available 9.4T postmortem MRI were used to delineate subfields CA1, subiculum and entorhinal cortex. Deep learning method StarDist was used to detect star‐shaped objects in thionine slides, combined with weakly‐supervised learning to identify artifact‐free cortical regions and Gaussian mixture modeling to distinguish neurons from glia (Figure 1AB). Validation against stereology measures of neuronal/glial density was performed in 50 separate regions. Neuronal measures were compared to MTL volume and thickness measures extracted from MRI. Result Automated neuronal density estimates (r=0.72, Figure 1C) agreed with stereology, but not glial density. Estimated number and size of neurons in CA1 and ERC were higher in individuals with less CA1/ERC atrophy (Figure 2) consistent with greater neuronal loss in advanced AD and LATE. However, CA1 neuronal and glial density, and ERC glial density, were higher in individuals with greater atrophy, suggesting tighter packing of neurons in remaining tissue and significant contribution of neuropil loss to MRI‐based atrophy measures. Pointwise analysis in Figure 3 shows patterns of association between regional MTL thickness and CA1 neuronal count, size, and density measures. Conclusion These initial feasibility results in two sections in 24 brain donors encourage us to apply this pipeline to a larger dataset of paired postmortem MRI and serial histology sections (Ravikumar et al., 2024) and to study associations between tau pathology, neuronal loss, and MRI‐based measures of atrophy, with the aim of better differentiating atrophy linked to LATE and AD.

Background Hippocampal Sclerosis of aging (HS) refers to age‐related selective neuronal loss and gliosis in hippocampal cornu ammonis 1 (CA1) and subiculum that is out of proportion to tau pathology in Alzheimer’s Disease (AD). HS is related to cognitive decline and memory impairments separately from other neurodegenerative pathologies. To date, in vivo imaging biomarkers of HS of aging are non‐existent, and their development would greatly improve diagnosis and prognosis in memory clinics. We therefore aimed to characterize the magnetic resonance imaging (MRI) signature of HS among autopsy confirmed cases of HS. Method Data consisted of same‐subject histological Nissl‐stained slices and postmortem MRI (0.2mm isotropic) acquired from 27 subjects at the University of Pennsylvania and University Castilla‐La Mancha. Based on neuropathological assessment, cases were grouped into HS (N = 5), intermediate to high AD neuropathologic change without HS (N = 10) and limited or no neuropathological burden (N = 12). We manually measured grey matter thickness and GM/WM intensity ratio in select locations across the hippocampal head, body, and tail. We also obtained more global structural measures from hippocampal subfields using an automated postmortem atlas‐based segmentation algorithm. Result Qualitatively, HS is clearly noticeable as cortical thinning and hypointense signal (approximating white matter) on postmortem MRI across the CA1 and subiculum, particularly anteriorly closer to the border between CA1/subiculum (Figure 1). Manual thickness measures showed complete separation between the HS group and the two reference groups across both the hippocampal head and body, and a less pronounced difference in the tail. Global structural measures from automated segmentations corroborated these group differences showing complete separation in CA1 thickness and significant differences in subiculum and the white matter layer of CA1 (Stratum Radiatum Lacunosum Moleculare, SRLM). Conclusion In MRI, HS is marked by hypointense voxels and cortical thinning across CA1 and subiculum. Both local manual thickness measurements and thickness measures of whole subfields derived from automatic segmentations provided promising results. As a next step, we plan to perform similar measurements on antemortem MRI of the same subjects, with the hopes of making progress toward an in vivo MRI biomarker of HS.

Background The amygdala is a hotspot for neuropathologies; however, it is unclear 1) which neuropathologies lead to amygdala neurodegeneration, 2) what specific amygdala subnuclei are affected, and 3) if the neuropathologies related to amygdala volume are local (inside the amygdala), or distal (in other regions). We investigate the relationships between different neuropathologies (tau, amyloid‐β [Aβ], α‐synuclein [α‐syn], and transactive response DNA‐binding protein 43 [TDP‐43]) and amygdala volumes. Method We analyzed postmortem data from 73 individuals with and without neurodegenerative diseases (age: 77±11 [45–101] years; 26 [36%] females; 51 [70%] cognitively impaired). Volumes of the whole amygdala and three amygdala subregions (lateral, B/Ab [basal/accessory basal], Co/Me/Ce [cortical/medial/central] nuclei: for n=24 individuals) were manually segmented on 0.2x0.2x0.2 mm3 postmortem magnetic resonance images (Figure 1). We used semiquantitative scores (0–3) of Aβ, tau, α‐syn, and TDP‐43 in the amygdala, the dentate gyrus (DG), the Cornu Ammonis 1 and subiculum (CA1/SUB), the entorhinal cortex (ERC), and averaged between the medial temporal lobe (MTL) regions (excluding the amygdala). Partial Spearman correlations were performed to investigate the relationships between neuropathologies and amygdala volumes, adjusting for age, sex, and other pathologies. Results Higher ratings of amygdala TDP‐43, MTL TDP‐43, and MTL tau were associated with smaller whole amygdala volume (Figure 2A–B, Figure 3A). However, MTL TDP‐43 was no longer significant when adjusting for amygdala TDP‐43 (Figure 3B). As MTL tau was associated with amygdala volume, we looked into which MTL subregions could be responsible for this association. Here, tau in DG, CA1/SUB, and ERC were all negatively associated with whole amygdala volume (Figure 2B). For exploratory subregional analyses, amygdala α‐syn was initially associated with B/Ab volume (Figure 2C, Figure 3C), but this correlation did not survive FDR‐correction. Conclusions These preliminary results indicate that TDP‐43 has a local effect on whole amygdala volume, whereas tau seems to affect amygdala volume distantly through other MTL regions, with the largest effect seen in DG tau, followed by CA1/SUB and ERC. Subregional analyses will be updated once a larger sample is available, as well as further analyses on non‐MTL regions.

Background Hippocampal Sclerosis of aging (HS) refers to age‐related selective neuronal loss and gliosis in hippocampal cornu ammonis 1 (CA1) and subiculum that is out of proportion to tau pathology in Alzheimer’s Disease (AD). HS is related to cognitive decline and memory impairments separately from other neurodegenerative pathologies. To date, in vivo imaging biomarkers of HS of aging are non‐existent, and their development would greatly improve diagnosis and prognosis in memory clinics. We therefore aimed to characterize the magnetic resonance imaging (MRI) signature of HS among autopsy confirmed cases of HS. Method Data consisted of same‐subject histological Nissl‐stained slices and postmortem MRI (0.2mm isotropic) acquired from 27 subjects at the University of Pennsylvania and University Castilla‐La Mancha. Based on neuropathological assessment, cases were grouped into HS (N = 5), intermediate to high AD neuropathologic change without HS (N = 10) and limited or no neuropathological burden (N = 12). We manually measured grey matter thickness and GM/WM intensity ratio in select locations across the hippocampal head, body, and tail. We also obtained more global structural measures from hippocampal subfields using an automated postmortem atlas‐based segmentation algorithm. Result Qualitatively, HS is clearly noticeable as cortical thinning and hypointense signal (approximating white matter) on postmortem MRI across the CA1 and subiculum, particularly anteriorly closer to the border between CA1/subiculum (Figure 1). Manual thickness measures showed complete separation between the HS group and the two reference groups across both the hippocampal head and body, and a less pronounced difference in the tail. Global structural measures from automated segmentations corroborated these group differences showing complete separation in CA1 thickness and significant differences in subiculum and the white matter layer of CA1 (Stratum Radiatum Lacunosum Moleculare, SRLM). Conclusion In MRI, HS is marked by hypointense voxels and cortical thinning across CA1 and subiculum. Both local manual thickness measurements and thickness measures of whole subfields derived from automatic segmentations provided promising results. As a next step, we plan to perform similar measurements on antemortem MRI of the same subjects, with the hopes of making progress toward an in vivo MRI biomarker of HS.

Background The amygdala is a hotspot for neuropathologies; however, it is unclear 1) which neuropathologies lead to amygdala neurodegeneration, 2) what specific amygdala subnuclei are affected, and 3) if the neuropathologies related to amygdala volume are local (inside the amygdala), or distal (in other regions). We investigate the relationships between different neuropathologies (tau, amyloid‐ß [Aß], a‐synuclein [a‐syn], and transactive response DNA‐binding protein 43 [TDP‐43]) and amygdala volumes. Method We analyzed postmortem data from 73 individuals with and without neurodegenerative diseases (age: 77±11 [45–101] years; 26 [36%] females; 51 [70%] cognitively impaired). Volumes of the whole amygdala and three amygdala subregions (lateral, B/Ab [basal/accessory basal], Co/Me/Ce [cortical/medial/central] nuclei: for n = 24 individuals) were manually segmented on 0.2×0.2×0.2 mm3 postmortem magnetic resonance images (Figure 1). We used semiquantitative scores (0‐3) of Aß, tau, a‐syn, and TDP‐43 in the amygdala, the dentate gyrus (DG), the Cornu Ammonis 1 and subiculum (CA1/SUB), the entorhinal cortex (ERC), and averaged between the medial temporal lobe (MTL) regions (excluding the amygdala). Partial Spearman correlations were performed to investigate the relationships between neuropathologies and amygdala volumes, adjusting for age, sex, and other pathologies. Results Higher ratings of amygdala TDP‐43, MTL TDP‐43, and MTL tau were associated with smaller whole amygdala volume (Figure 2A–B, Figure 3A). However, MTL TDP‐43 was no longer significant when adjusting for amygdala TDP‐43 (Figure 3B). As MTL tau was associated with amygdala volume, we looked into which MTL subregions could be responsible for this association. Here, tau in DG, CA1/SUB, and ERC were all negatively associated with whole amygdala volume (Figure 2B). For exploratory subregional analyses, amygdala a‐syn was initially associated with B/Ab volume (Figure 2C, Figure 3C), but this correlation did not survive FDR‐correction. Conclusions These preliminary results indicate that TDP‐43 has a local effect on whole amygdala volume, whereas tau seems to affect amygdala volume distantly through other MTL regions, with the largest effect seen in DG tau, followed by CA1/SUB and ERC. Subregional analyses will be updated once a larger sample is available, as well as further analyses on non‐MTL regions.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of school-age children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no individual variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 ADHD cases and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, revealing new and important information on the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes, as well as around brain-expressed regulatory marks. These findings, based on clinical interviews and/or medical records are supported by additional analyses of a self-reported ADHD sample and a study of quantitative measures of ADHD symptoms in the population. Meta-analyzing these data with our primary scan yielded a total of 16 genome-wide significant loci. The results support the hypothesis that clinical diagnosis of ADHD is an extreme expression of one or more continuous heritable traits.