bluuebunny/crossref_metadata_2025_split huggingface dataset:
The reliability of a deep learning model in external memory clinic MRI data: A multi‐cohort study
Authors: Mårtensson Gustav , Ferreira Daniel , Granberg Tobias , Cavallin Lena , Oppedal Ketil , Padovani Alessandro , Rektorova Irena , Bonanni Laura , Pardini Matteo , Kramberger Milica G. , Taylor John‐Paul , Hort Jakub , Snædal Jón , Kulisevsky Jaime , Blanc Frédéric , Antonini Angelo , Mecocci Patrizia , Vellas Bruno , Tsolaki Magda , Kloszewska Iwona , Soininen Hilkka , Lovestone Simon , Simmons Andrew , Aarsland Dag , Westman Eric 
Published: December 2020

AbstractBackgroundDeep learning (DL) has provided impressive results in numerous domains in recent years, including medical image analysis. Training DL models requires large data sets to yield good performance. Since medical data can be difficult to acquire, most studies rely on public research cohorts, which often have harmonized scanning protocols and strict exclusion criteria. This is not representative of a clinical setting. In this study, we investigated the performance of a DL model in out‐of‐distribution data from multiple memory clinics and research cohorts.MethodWe trained multiple versions of AVRA: a DL model trained to predict visual ratings of Scheltens' medial temporal atrophy (MTA) scale (Mårtensson et al., 2019). This was done on different combinations of training data—starting with only harmonized MRI data from public research cohorts, and further increasing image heterogeneity in the training set by including external memory clinic data. We assessed the performance in multiple test sets by comparing AVRA’s MTA ratings to an experienced radiologist’s (who rated all images in this study). Data came from Alzheimer’s Disease Neuroimaging Initiative (ADNI), AddNeuroMed, and images from 13 European memory clinics in the E‐DLB consortium.ResultsModels trained only on research cohorts generalized well to new data acquired with similar protocols as the training data (weighted kappa κw between 0.70‐0.72), but worse to memory clinic data with more image variability (κw between 0.34‐0.66). This was most prominent in one specific memory clinic, where the DL model systematically predicted too low MTA scores. When including data from a wider range of scanners and protocols during training, the agreement to the radiologist’s ratings in external memory clinics increased (κw between 0.51‐0.71).ConclusionIn this study we showed that increasing heterogeneity in training data improves generalization to out‐of‐distribution data. Our findings suggest that studies assessing reliability of a DL model should be done in multiple cohorts, and that softwares based on DL need to be rigorously evaluated prior to being certified for deployment to clinics. References: Mårtensson, G. et al. (2019) ‘AVRA: Automatic Visual Ratings of Atrophy from MRI images using Recurrent Convolutional Neural Networks’, NeuroImage: Clinical. Elsevier, 23(March), p. 101872.
Neuroprotection of cholinergic neurons with tau aggregation inhibitor and rivastigmine in L1 mice with Alzheimer’s‐like tauopathy
Authors: Steczkowska Marta , Zadrozny Maciej , Wydrych Malgorzata , Gasiorowska Anna , Niewiadomski Wiktor , Riedel Gernot , Wischik Claude M. , Niewiadomska Grazyna 
Published: December 2020

AbstractBackgroundBasal forebrain cholinergic dysfunction, likely linked to tau aggregation pathology, is a characteristic feature of AD. Cholinergic neurons contain choline acetyltransferase (ChAT) and high‐affinity tropomyosin‐related kinase A (TrkA) and send efferents to cortex and hippocampus where they release acetylcholine (ACh). The vesicular acetylcholine transporter (VAChT) is responsible for loading ACh into secretory vesicles and acetylcholine esterase (AChE) hydrolyses ACh in the synaptic cleft. We here aimed to evaluate the cholinergic phenotype in the Line 1 animal model of tauopathy and to determine the effect of the choline esterase inhibitor rivastigmine alone and in conjunction with the tau aggregation inhibitor hydromethylthionine on the cholinergic system.MethodLine 1 (L1) and control NMRI mice, 8‐9 months old, divided into 13 groups (n = 5 each), were treated with rivastigmine (0.1 and 0.5 mg/kg) and hydromethylthionine (5 and 15 mg/kg) and their combinations for 11 weeks. Immunohistochemical staining in brain sections was performed for ChAT, TrkA, VAChT and tau with a repeat domain monoclonal antibody (TauRx Therapeutics Ltd.). AChE activity was measured histochemically. The state of the cholinergic system was determined by stereological counting of ChAT‐ir and TrkA‐ir neurons, while Relative Optical Intensity (ROI) was used to tau immunoreactivity in basal forebrain, and cholinergic projections were evaluated using VAChT and AChE ROI.ResultNumber of ChAT‐ir, TrkA‐ir neurons and ROI value for VAChT and AChE were significantly lower while ROI value for tau was higher in vehicle‐treated L1 mice compared with wild type control. Numbers of ChAT‐ir, TrkA‐ir neurons and ROI value of VAChT and AChE in L1 mice were increased and tau ROI was decreased by hydromethylthionine treatment. Combined treatment decreased numbers of ChAT‐ir, TrkA‐ir neurons and ROI for VAChT and AChE compared to L1 groups treated with hydromethylthionine alone.ConclusionThere was a significant loss of cholinergic basal forebrain neurones, impaired cholinergic projection and increased tau staining in L1 mice. Monotherapy with hydromethylthionine improved the cholinergic neurons phenotype, enhanced their projection and reduced tau pathology. Combination therapy interacted negatively attenuating the effect of hydromethylthionine given alone.
Influence of microglial activation on structural and functional connectivity in mild cognitive impairment subjects
Authors: Leng Fangda , Hinz Rainer , Dani Melanie , Hampshire Adam , Gentleman Steve , Brooks David J. , Edison Paul 
Published: December 2020

AbstractBackgroundActivated microglia is present in both Alzheimer’s subjects (AD) and mild cognitive impairment (MCI) subjects and can be visualised by both pathological evaluation and in‐vivo imaging studies. It has been established that neuroinflammation plays a vital role in Alzheimer’s trajectory and disruption in structural and functional connectivity is also a key event in Alzheimer’s disease. However, the mechanism by which microglial activation influence brain structural and functional connectivity remains to be elucidated. 11C‐PBR28 PET is a marker of translocator protein (TSPO) reflecting microglial activation and 18F‐Flutematemol PET is a marker of amyloid deposition.Method25 amnestic MCI and 17 healthy controls (HC) were recruited and underwent T1‐weighted, diffusion tensor and resting‐state functional MRI, 11C‐PBR28 and 18F‐Flutemetamol PET scans. 11C‐PBR28 and 18F‐Flutemetamol scans were analysed using target‐to‐cerebellar ratio. Tract‐Based Spatial Statistics was performed on DTI scans. RS‐fMRI scans were analysed using medial prefrontal cortex (MPFC) as a seed. The relationship between tracer uptake and structural integrity of white matter tracts or brain functional connectivity with MPFC was analysed using linear regression corrected for age and gender.ResultMCI cohort showed significantly decreased functional connectivity between MPFC and posterior cingulate and precuneous regions. Cortical 11C‐PBR28 uptake but not 18F‐Flutemetamol was negatively correlated with FA in the corpus callosum, bilateral inferior frontal‐occipital fasciculi and inferior longitudinal fasciculi. MPFC 11C‐PBR28 uptake was correlated with increased MPFC functional connectivity to anterior frontal regions and reduced connectivity to posterior frontal, temporal, parietal and cingulate regions; while frontal amyloid load was correlated with reduced MPFC connectivity with frontal and temporal cortices. Regression analysis with both 18F‐Flutemetamol and 11C‐PBR28 demonstrated that MPFC 11C‐PBR28 was significantly associated MPFC connectivity with posterior frontal, parietal and cingulate regions.ConclusionThe findings suggest that MPFC microglial activation is associated with increased functional connectivity with the nearby regions and decreased connectivity with the distal regions to MPFC in MCI subjects. Findings from DTI analysis showed negative correlation with structural integrity of the long fibre tracts which are connecting distal regions. These findings suggest that neuroinflammation is involved in the structural and functional connectivity disruption and probably remodelling in AD trajectory.
Specific targeting of a highly toxic subpopulation of Aβ42 oligomers for the treatment of Alzheimer’s disease
Authors: Sandberg Anders , Rodriguez Rosa Crespo , Kettunen Petronella , Rosengren Malin , Correa Ernesto Berenjeno , Morrema Tjado , Hoozemans Jeroen J.M. , Scheper Wiep 
Published: December 2020

AbstractBackgroundNon‐clinical data on the etiology of Alzheimer’s disease (AD) suggest that only a very small fraction of soluble oligomeric Aβ42 carries most of the neurotoxic potency. But the study of Aβ42 soluble species has been hampered by their intrinsic heterogeneous and dynamic nature. A unique oligomer‐stabilizing technology, AβCC, enables the development of therapies that target these specifically. We here demonstrate the development such immunotherapies that exhibit unique Aβ oligomer targeting activity which translates into high efficacy in non‐clinical models of the disease.MethodStable synthetic Aβ42CC peptide oligomer derivatives were used as antigens in an active vaccine and were used to develop a murine monoclonal antibody, ALZ‐201. Efficacy was evaluated on brain extracts from AD patients and controls. These brain extracts were immunodepleted with ALZ‐201 and control antibodies. Toxicity assays were then performed in primary mouse neuronal cultures using an automated cell imaging platform. In addition, acute neurotoxicity effects on memory formation in zebrafish were assessed following intracranial injections of the brain extracts.ResultThe AβCC oligomers were able to generate truly oligomer‐specific antibodies. AD extracts exhibited higher levels of toxicity in contrast to non‐AD extracts in both cells assays and in zebrafish. This toxicity was highly dependent on Aβ, shown by immunodepletion with 4G8. Comparable toxicity was observed for brain extracts immunodepleted with ALZ‐201 as for extracts immunodepleted with 4G8. Interestingly, the soluble Aβ42 species captured by ALZ‐201 were below the limit of detection with the standard biochemical techniques used for analysis.ConclusionThe data support the hypothesis that a specific subtype of Aβ42 oligomers has large neurotoxic effects in the central nervous system that can affect synaptic plasticity, learning and memory. These oligomers are present in very small amounts and, due to the inaccessible environment, are not likely to be targeted with non‐specific anti‐Aβ immunotherapies. In contrast, targeting them specifically may serve as effective future treatments.
Joint trajectories of episodic memory and odor identification in older adults: Patterns and determinants
Authors: Dintica Christina S. , Haaksma Miriam L. , Olofsson Jonas , Bennett David A. , Xu Weili 
Published: December 2020

AbstractBackgroundEmerging evidence suggests that olfactory function is closely linked to memory function. The aims of this study were to assess whether olfactory and episodic memory functions follow similar age‐related decline trajectories, to identify different patterns of decline, as well as determinants of the patterns.MethodsUsing data from the Rush Memory and Aging Project, 1023 dementia‐free participants were identified at baseline and followed for up to 8 years with annual assessments for episodic memory (composite of 7 tests) and odor identification (Brief Smell Identification Test). Data on demographics, medical conditions, social and lifestyle factors were collected by self‐report or medical examination. Trajectories of episodic memory and olfactory function were first modeled individually and then jointly over time using growth mixture models, to identify latent classes (patterns) of the joint trajectories. Multivariate logistic regression was used to identify predictors of the patterns.ResultsBoth episodic memory and olfactory function showed similar trends over the follow‐up interval. Three distinct patterns of joint trajectories, across both functions, were identified; Class 1‐ stable average performance in both functions (n=690, 67.4%); Class 2‐ stable average episodic memory and declining odor identification (n=231, 22.6%); and Class 3‐ decline in both functions (n= 102, 10.0%). Compared to Class 1, people in Class 2 were more likely to be older and male. People in Class 3 were more likely to be older, apolipoprotein ε4 carriers, participate less in cognitive activity, and have lower BMI.ConclusionsEpisodic memory and olfactory function often show similar trajectories in aging, which can be jointly characterized as stable, olfactory decline only, and joint decline.
Is it time to use predictive models to boost power of Alzheimer’s disease clinical trials? A post‐hoc analysis of phase 3 solanezumab trials
Authors: Ezzati Ali , Davatzikos Christos , Wolk David A. , Aisen Paul S. , Lipton Richard B. 
Published: December 2020

AbstractBackgroundThe ideal participants for Alzheimer’s disease (AD) clinical trials would show cognitive decline in the absence of treatment (i.e. placebo arm) and would also respond to the therapeutic intervention. However, up to 50% of placebo treated participants enrolled in the AD clinical trials do not show cognitive or functional decline during the timeframe of trials. One strategy to boost the power of trials is to exclude individuals who are not likely to progress using data‐driven predictive models. In this study, we aimed to investigate if using machine learning (ML) predictive models can be an effective tool for enriching enrollment in AD trials.MethodWe used data from 769 patients from the placebo arm of two phase 3, double‐blind trials of EXPEDITION (N=367) and EXPEDITION2 (N=402). Patients had 18 months of follow‐up. Ensemble linear discriminant ML models were developed using EXPEDITION data to classify participants as 1) cognitive decliners, change of >0 from baseline in the Alzheimer’s Disease Assessment Scale cognitive subscale (ADAS‐cog) score, versus stable cognition, change of £0 from baseline ADAS‐cog score; or 2) functional decliners, change of <0 from baseline in the Alzheimer's Disease Cooperative Study ‐ Activities of Daily Living (ADCS‐ADL) versus stable function, change of ≥0 from baseline ADCS‐ADL, at both 15 and 18 months of follow‐up. Data from EXPEDITION2 were used to validate models. Features used in ML models included baseline demographics, Apo4 genotype, neuropsychological scores, functional scores and volumetric MRI.ResultIn EXPEDITION and EXPEDITION2 trials, 45.2% and 42.0% of participants in the placebo arm did not show cognitive decline, respectively (Table 1). Models had high sensitivity and modest specificity in both the training (EXPEDITION) and (EXPEDITION2) samples for detecting the stable group. Positive predictive value of models was higher than the base prevalence of cognitive or functional decline, and negative predictive value of models were higher than the base rate of participants who had stable cognition or function (Tables 2 and 3).ConclusionPredictive models may boost the power of AD trials through selective inclusion of participants expected to decline and exclusion of those expected to remain stable.
Understanding meaningful symptoms and challenges in people with Down syndrome and dementia: A qualitative study of caregivers’ perspectives
Authors: Knox Kari , Stanley Justin , Hendrix James A , Hillerstrom Hampus , Achenbach Jillian , Chicoine Brian , Lai Florence , Lott Ira T , Rockwood Kenneth 
Published: December 2020

AbstractBackgroundPeople with Down syndrome are at an increased risk of developing Alzheimer’s Disease. As many more individuals with Down syndrome are now living into older adulthood, the prevalence of Alzheimer’s disease has risen significantly in this group. Identifying dementia symptoms in this setting can be daunting due to heterogeneous baseline function, cognition, and behaviour. Here, we interviewed caregivers to elicit their impressions of the most meaningful symptoms and challenges for people with Down Syndrome and dementia.MethodInitially, a dementia symptom menu was adapted for Down syndrome by four expert clinicians. We then recruited 10 caregivers of people with Down syndrome and dementia. Semi‐structured interviews began with open‐ended discussion of symptoms and challenges, followed by an in‐depth menu review. Interviews were facilitated by a research nurse, audio recorded and transcribed verbatim. Transcripts were reviewed by two researchers who coded quotes independently. Codes were discussed to identify emergent themes.ResultCaregivers ranged from 54‐77 years of age (median 65). Most were female (9/10) with ≥15 years of education (10/10). The person they cared for was 52‐61 years (median 58) with Down syndrome and a formal diagnosis (6/10) or clinical suspicion (4/10) of dementia. Chiefly, two themes were identified: caregiver burden and healthcare difficulties. Caregiver burden was expressed in many ways such as increased responsibilities, financial impact and emotional toll. Caregivers also described challenges with medical professionals who were not well‐equipped for these patients (“One [physician] was very honest with me and said ‘I have to tell you; I have no clinical experience with this’”). This was particularly noted by caregivers in rural areas. When asked to list their five most meaningful symptoms, caregivers reported behavioural changes (13/50, e.g. irritability/frustration) followed by cognitive decline (12/50, e.g. verbal repetition) and physical manifestations (11/50, e.g. incontinence).ConclusionIn eliciting views about the most meaningful symptoms and challenges, semi‐structured interviews identified two main themes: caregiver burden and healthcare difficulties. Although in people without Down syndrome cognitive decline is the hallmark of dementia, here caregivers interviewed frequently reported changes in behaviour and physical manifestations as most meaningful.
Dynactin 6 deficiency enhances tubular ER‐associated dystrophic neurites formation
Authors: Sharoar Md. Golam , Yan Riqiang 
Published: December 2020

AbstractBackgroundThe formation of dystrophic neurites (DNs) is a contributing factor to synaptic dysfunction in Alzheimer’s disease (AD) patients’ brains. We have shown that tubular endoplasmic reticulum (ER) shaping proteins reticulon 3 (RTN3), REEP2 and REEP5 are participated in the formation DNs, named as RTN3 immunoreactive DNs or RIDNs. RIDNs are appeared as clustered or dispersed forms in AD and aging mouse brain, respectively. Ultrastructural investigation showed that RIDNs are constitute with abnormal clustering of tubular ER. The over expression of RTN3 accelerates aging associated disperse RIDNs formation in Tg‐RTN3 mouse brain hippocampus. To determine a molecule that may cause RTN3 mediated abnormal tubular ER clustering, we aimed to identify RTN3 interacting proteins and to elucidate its functional roles in tabular ER accumulation and RIDNs formation in aging and AD brain.MethodsYeast two‐hybrid system, co‐immunoprecipitation, domain mapping and immune‐confocal studies to identify RTN3 interacting proteins. WB was performed to measure the protein level. Formation of RIDNs in mouse brains were detected using immuno‐confocal study. AAV9‐RTN3‐mCherry and AAV9‐DCTN‐GFP were injected at hippocampus of wild type mice to over expressed RTN3 and DCTN6.ResultsWe have identified that N‐terminal domain of RTN3 interacts with dynactin 6 (DCTN6), a protein component that involved in dynein‐mediated retrograde transport of cargo vesicles. Our immune‐confocal studies on DCTN6 and RTN3 over expressed cells and primary cultured neuron indicate that RTN3‐DCTN6 interaction likely mediates the tubular ER trafficking. The DCTN6 protein level decreases during aging and it reduces in hippocampus compared to cortical samples of the same age mice. To understand the functional roles of DCTN6 in RIDNs formation during aging and beta‐amyloid plaque deposition, DCTN6 deficient Tg‐RTN3 and 5xFAD mice were generated. Tg‐RTN3; DCTN6+/‐ showed reduced DCTN6 protein level and enhanced hippocampus specific RINDs formation compare to Tg‐RTN3; DCTN6+/+ mouse. We are investigating whether RIDNs formation are increases in DCTN6 deficient 5xFAD mice and whether AAV9‐DCTN6 overexpression reduces RIDNs formation in AAV9‐RTN3 overexpressed mouse brain.ConclusionRTN3‐DCTN6 interaction likely mediates the tubular ER transport in axons and the DCTN6 deficiency is a contributing factor for tubular ER accumulation, RIDNs formation in AD and aging brain.
3D‐chemocentric target deconvolution of unprecedented anti‐inflammatory drug scaffolds
Authors: Kim Mi‐hyun , Dhorma Lama Prema , Teli Mahesh Kumar , Venkanna Arramshetti 
Published: December 2020

AbstractBackgroundA typical hit‐to‐lead flow focuses on a well‐established molecular target. However, imperfect pathological backgrounds of the diseases can bring out low confidence on the chosen target. Therefore, despite unclear targets, the regulation of neuroinflammation is an important approach of early stage drug discovery in AD and neurological disorders. The potential targets of anti‐inflammatory agents are enormous but don't be clear investigated with their atomic level mechanism.MethodChOS (Chemistry‐oriented synthesis), a kind of inverse drug design, suggests target deconvolution of unprecedented anti‐inflammatory agents (in‐house compounds) through 3D‐chemocentric approach.ResultThe inverse approach identified an in‐house anti‐inflammatory agent, as the first‐in‐class small molecule antagonist for non‐histaminergic neurons, investigated a new therapeutic indication of a known target, and provided pharmacological profile of in‐house anti‐inflammatory agents.ConclusionThe inverse drug discovery approach of in‐house anti‐inflammatory agents, ChOS, can be a compensatory alternative for neurological disorders and the results wait for AD & dementia collaboration.