bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reducing MRI Inter‐Scanner Variability Using 3D Superpixel ComBat
Authors: Chen Chang‐Le , Torbati Mahbaneh Eshaghzadeh , Wilson James D , Minhas Davneet S , Laymon Charles M , Hwang Seong Jae , Maillard Pauline , Fletcher Evan , DeCarli Charles S. , Tudorascu Dana L 
Published: December 2022

AbstractBackgroundInter‐scanner variability hinders the direct comparability of multi‐site/scanner MRI data for clinical research. The ComBat method is commonly used to reduce the variability based on an empirical Bayes framework1,2, harmonizing the data at the feature level (e.g., region‐of‐interest measures). However, directly harmonizing the scans at the voxel‐level using ComBat has been relatively less explored. In this study, we investigated the performance of the voxel‐wise ComBat. Also, going beyond voxels, we proposed a new ComBat approach which operates on a small group of voxels called superpixels3.MethodEighteen subjects (10 patients with Alzheimer's disease and 8 controls; age: 68.0 [9.3] years; 10 females) participated in this study. For each subject, T1‐weighted images were acquired on each of four 3T scanners with different manufacturers or models (i.e., GE, Philips, Siemens‐Prisma, Siemens‐Trio). After the standard image preprocessing including two‐step registration by using the Statistical Parametric Mapping (SPM12)4, the unharmonized scans (Raw data) were aligned in the standard template space. To reduce the computational load for ComBat at the voxel level (Voxel‐ComBat), we used a three‐dimensional superpixel algorithm3 to parcellate the images into hundreds of superpixels based on the study‐specific template, and then the ComBat was applied at the superpixel level (Figure 1). Compared to Voxel‐Combat operating on about half million voxels (computation time >>10,000 seconds), this superpixel ComBat (SP‐ComBat) operates on only a few hundred superpixels, significantly improving the computation efficiency (computation time < 5 seconds) while maintaining the harmonization performance. The harmonized scans were used to estimate cortical thickness by employing surface‐based morphometry5, and the coefficients of variation of thickness measures were calculated to evaluate the harmonization performance.ResultThe harmonized data provided similar contrasts across scanners compared to the Raw images in visual inspection (Figure 2) and had comparable distributions of the tissue‐specific signal intensity between scanners for both Voxel‐ComBat and SP‐ComBat (Figure 3). Also, these two methods significantly reduced the inter‐scanner variation (both p‐values < 0.001) in terms of cortical thickness measures (Figure 4).ConclusionThis study evaluated the feasibility and effectiveness of Voxel‐ComBat and proposed a new approach, SP‐ComBat, to optimize the efficiency of ComBat harmonization at the voxel level.
A novel, efficient and seamless Phase 2A‐2B design to test varoglutamstat in early AD: the VIVA‐MIND study
Authors: Messer Karen , Jacobs Diane M. , Salmon David P. , Qiu Yuqi , Revta Carolyn , Weber Frank , Kuhn‐Wache Kerstin , Leger Gabriel C. , Feldman Howard H. 
Published: December 2022

AbstractBackgroundImproved Phase 2 study designs may increase success rates in late stage AD trials. Varoglutamstat (PQ912) is an oral small molecule glutaminyl cyclase inhibitor designed to address several key disease mechanisms. A Phase 2A study (NCT02389413) of 120 early AD patients treated for 12 weeks provided preliminary evidence of safety and tolerability, and effects on working memory, CSF biomarkers, and synaptic function (EEG theta‐power).ObjectiveTo design a well‐powered, safe, and efficient study of varoglutamstat in early AD incorporating adaptive dose selection in Phase 2A, a futility analysis testing pharmacological, biological and cognitive criteria, and a seamless transition to a larger Phase 2B study investigating longer‐term efficacy and safety.MethodsAn efficient and safe selection rule across 3 descending doses (600mg, 300mg, 150 mg BID) was established using a continuously monitored Pocock safety boundary targeting a set of treatment emergent AE’s of interest. Well‐powered stage‐gate criteria at a planned interim futility analysis included thresholds for target occupancy in plasma, and would detect negative effects on a cognitive composite or absence of benefit on EEG theta‐power. The Phase 2B study was powered to detect an effect size of 0.7 points on the Clinical Dementia Rating – Sum of Boxes score at 18 months, an established approvable endpoint.ResultsThe on‐going Phase 2A adaptive dose‐finding trial (NCT03919162) is randomizing 180 subjects with MCI or mild probable AD, initially to 24+ weeks of 600mg varoglutamstat dose or placebo, BID. If the safety boundary is hit, the dose will be discontinued and all subjects titrated down, with similar sequential testing of lower doses as needed. The interim futility analysis will occur when the first 180 randomized subjects have been on study for at least 24 weeks. If this stage‐gate is passed, Phase 2B will enroll 234 additional patients to achieve 414 total patients treated for 72 weeks at full dose of varoglutamstat or placebo.ConclusionThis novel study design enables adaptive dose selection, an early interim futility analysis, and longer‐term determination of cognitive and functional efficacy, and should support robust proof‐of‐concept for varoglutamstat using a total sample of 414 subjects treated for 72 weeks.
Development and evaluation of Simvastatin based SNEDDS for treatment of Alzheimer’s disease
Authors: Hardeep   , Pandey Narendra Kumar 
Published: December 2022

AbstractBackgroundThe purpose of this research work to improve solubility and bioavailability of Simvastatin using self nano‐emulsifying drug delivery system (SNEDDS) for treatment the Alzheimer’s disease.MethodSelf emulsifying property of various oils including essential oils was evaluated with suitable surfactants and co‐surfactants. Validation of method for accuracy, repeatability, Interday and intraday precision, ruggedness, and robustness were within the acceptable limits. The liquid SNEDDS was prepared and optimized using ternary phase diagram, thermodynamic, centrifugation and cloud point studies.ResultThe globule size of optimized formulations was less than 200 nm which could be acceptable nanoemulsion size range. The mean droplet size, drug loading, PDI and zeta potential were found to be 141.0 nm, 92.22%, 0.23 and ‐10.13 mV and 153.5nm, 93.89%,0.41 and ‐11.7 mV and 164.26 nm, 95.26%, 0.41 and ‐10.66mV respectively. The best formulations were subjected to FESEM for surface morphology.ConclusionFormulation development, and evaluation of simvastatin loaded self nano‐emulsifying drug delivery system (SNEDDS) for treatment the Alzheimer’s disease were carried out.
Machine learning for Alzheimer’s disease classification from genomic tiling variants
Authors: Lee Matthew , Lee Brian N , Zaranek Sarah Wait , Bao Jingxuan , Yang Shu , Jung Sang‐Hyuk , Huang Heng , Saykin Andrew J. , Thompson Paul M , Davatzikos Christos , Kim Dokyoon , Zaranek Alexander Wait , Shen Li ,   for the Alzheimer's Disease Neuroimaging Initiative and the AI4AD Initiative
Published: December 2022

AbstractBackgroundAs machine learning (ML) technologies make improving strides, they’ve demonstrated advantageous novelties in the understanding and prediction of Alzheimer’s Disease (AD). Recent efforts in AD research have aimed to capitalize ML for AD genomics. Whole‐genome tiling (WGT) establishes a new representation of whole‐genome sequencing (WGS) data, one that has been brought forth in support of ML and precision medicine.MethodA comprehensive description, workflow, and publicly available WGT data can be found at https://curii.co/su92l-j7d0g-swtofxa2rct8495. In this work, we analyzed the ADNI WGT data, and first performed quality control, imputation, and one‐hot encoding to each tile and the respective tile variants (Figure 1). Then, using the GWAS result from an independent cohort, we mapped the top ten most significant single‐nucleotide polymorphisms (SNPs) associated with AD, to their respective tiles. Using these tile data, we performed AD classification with an XGBoost algorithm. We then reiterated this process including covariates (age, sex, and ethnicity) with tiling variants. A total of 1,545, subjects (474 cases, 1,071 controls) were studied.ResultAfter mapping our 10 most significant SNPs from an independent GWAS study to WGT data. We ended up with 10 different tiles where those 10 tiles encapsulated 356 SNPs. In our comparative analysis we make AD diagnosis classifications using either our 10 tiles of WGT data, our 356 SNPs in WGS data, covariate data (age, sex, and ethnicity), or a combination of genomic data (tiles or SNPs) and covariates. Our results (Figure 2) show that WGT performs comparatively to that of SNPs, indicating the patterns embedded within individual SNPs and those within WGT data have similar discriminative power.ConclusionOur pilot investigation on the use of a small set of targeted WGT represented genomic data within the context of ML and AD classification has demonstrated similar performance to the SNP data. These results suggest that despite the differing information encapsulated within WGT data compared to WGS data, we are able to derive comparable results in AD classification. Our study on WGT and its use in AD machine learning shows the potentiality and novelty of WGT, and it warrants probing for further exploration of its maximal use.
Development of Novel Partial Mitochondrial Complex I Inhibitors as a Therapy for Alzheimer Disease.
Authors: Trushin Sergey , Stojakovic Andrea , Chang Su‐Youne , Macura Slobodan , Trushina Eugenia 
Published: December 2022

AbstractBackgroundConsistent failure of clinical trials for Alzheimer Disease (AD) emphasizes the necessity to identify novel therapeutic targets for this debilitating condition. We recently identified the mitochondrial complex I (MCI) as a small molecule druggable therapeutic target for AD.MethodUsing rational design and extensive structure‐activity relationship studies, we developed novel classes of partial MCI inhibitors with high selectivity, specificity, safety, and drug‐like properties. Target engagement, selectivity and specificity of new compounds were established using multiple in vitro assays, including surface plasmon resonance (SPR), competitive and direct binding, proteomics and pull down experiments. Using these techniques, we developed new lead compound C458 that was interrogated in in vivo efficacy studies in APP/PS1 mice.ResultWe demonstrated that the new lead C458 directly binds to MCI. A single dose administration of C458 to mice or treatment of primary mouse neurons activates AMPK‐a, Akt, autophagy, Sirtuins 1 and 3, and upregulates PGC‐1a leading to enhanced mitochondrial biogenesis. C458 has excellent oral bioavailability, blood–brain‐barrier penetrance, and was remarkably clean in the 250 kinase and CEREP 44 safety panels. Chronic administration of C458 (25 mg/kg/day in drinking water ad lib) to APP/PS1 mice for 6 months starting at pre‐symptomatic stage did not cause detectable side effects, and resulted in cognitive protection, improved long‐term potentiation, and decreased oxidative stress and inflammation. Furthermore, APP/PS1 mice treated with C458 showed a significant increase in glucose uptake and utilization in the brain detected with a translational in vivo biomarker FDG‐PET, as well as an enhancement of ATP production measured in vivo using 31P NMR.ConclusionMechanistic studies confirmed that C458 treatment triggered mitochondrial stress response augmenting mitochondrial biogenesis, anti‐oxidant signaling, and cellular energetics that ultimately restored energy brain homeostasis, leading to cognitive protection in a mouse model of AD. Our studies demonstrate that modulation of MCI activity using novel specific MCI inhibitors improves bioenergetics in the brain and averts cognitive decline representing novel therapeutic approach for AD.
Fosgonimeton, a novel, small molecule positive modulator of the HGF/MET system is neuroprotective in primary neuron culture
Authors: Reda Sherif , Johnston Jewel , Taylor Robert W , Church Kevin 
Published: December 2022

AbstractBackgroundPositive modulation of the hepatocyte growth factor (HGF)/MET system may represent a promising therapeutic strategy for several neurodegenerative disorders, including Alzheimer’s and Parkinson’s disease. Activation of the HGF/MET system induces neuroprotective effects that counteract neurotoxicity, neuroinflammation, and oxidative stress‐induced damage, all pathological hallmarks of neurodegeneration. Herein, we investigated the in vitro neuroprotective potential of fosgonimeton (ATH‐1017), a novel, small molecule positive modulator of the HGF/MET system that has demonstrated neurotrophic and pro‐cognitive effects in vitro and in vivo. In addition, we assayed several novel compounds with related activity to fosgonimeton to establish the neuroprotective effects of a series of HGF/MET positive modulators.MethodMature rat cortical neurons were treated with the active metabolite of fosgonimeton or related HGF/MET positive modulators and subjected to a variety of neurotoxic insults including 1‐methyl‐4‐phenylpryidinium (MPP+), glutamate, lipopolysaccharide (LPS), or hydrogen peroxide (H2O2). Neuronal cell viability was determined using CellTiter Glo luminescence assay to assess relative levels of ATP. Furthermore, the effect of fosgonimeton and other test compounds on mitochondrial membrane potential (MMP) was assessed utilizing a fluorescent MMP dye.ResultCortical neurons treated with our HGF/MET positive modulators exhibited significant improvement in cell viability against MPP+ neurotoxicity, glutamate excitotoxicity, LPS‐induced cytotoxicity, and H2O2‐induced oxidative stress. For example, treatment with 1 µM fosgonimeton rescued cell viability against neurological insults with the following percent recoveries: 85% vs. MPP+, 61% vs. glutamate, 93% vs. LPS, and 144% vs. H2O2. Significant improvement in cell viability was also observed at 100 nM, 10 nM, and 1 nM fosgonimeton against all insults, highlighting its potent neuroprotective actions. Furthermore, fosgonimeton treatment led to an increase in mitochondrial membrane potential, suggesting that it may mitigate mitochondrial dysfunction associated with neurodegeneration.ConclusionOur data demonstrate the ability of fosgonimeton and related HGF/MET positive modulators to offer protection against several neurological insults that are central to neurodegeneration. The neuroprotective effects of fosgonimeton, in addition to its neurotrophic and pro‐cognitive effects, highlight its therapeutic potential to restore neuronal health and slow or reverse neurodegeneration. Fosgonimeton is currently in clinical trials for Alzheimer’s disease, Parkinson’s disease dementia, and Dementia with Lewy bodies.
Comorbid Pathology in Clinical Trial Participants: Autopsy Findings and Clinical Features
Authors: Jicha Gregory A , Barber Justin M , Abner Erin L , Gold Brian T. , Kryscio Richard J , Schmitt Frederick A. , Van Eldik Linda J , Wilcock Donna M , Nelson Peter T 
Published: December 2022

AbstractBackgroundThe presence of multiple comorbid pathologic features in late onset dementia has been well documented across cohort studies that incorporate autopsy evaluation. It is likely that such mixed pathology may also be common in Alzheimer’s disease and related dementias (ADRD) clinical trial participants, potentially confounding the results of interventional trials that are designed to target a solitary pathophysiologic mechanism.MethodThe University of Kentucky Alzheimer Disease Research Center autopsy database was screened for participants that had previously engaged in therapeutic interventional trials for Alzheimer’s disease, vascular cognitive impairment and dementia, and/or ADRD prevention trials from 2005 to present. Seventy‐five cases (out of a total n = 546) had engaged in clinical trials for the prevention or treatment of ADRD. Pathologic features studied included b‐amyloid, tau, a‐synuclein, TDP‐43, and cerebrovascular disease using conventional rating scales.ResultAutopsy cases for those that previously engaged in clinical trials did not differ significantly from those that were trial‐naïve in respect to demographic, genetic (ApoE), or clinical characteristics with the exception of CDR global scores that were lower for past trial participants (p<0.05). Comorbid pathologies were common across study types with a mean of 3 pathologic features/participant, 18% with quadruple misfolded proteinopathy (QMP; Ab, tau, a‐synuclein, & TDP43), and only 34% of MCI/AD trial participants demonstrating a “pure” disease state that was targeted by the study intervention.ConclusionIn our study, approximately 2 out of 3 ADRD trial participants had comorbid mixed pathologic features. Understanding the heterogeneity of pathologies seen in clinical trial participants may allow improved I/E criteria based on clinical features and the rational use of antemortem biomarkers to stratify the likelihood of mixed comorbid pathology that may be unwanted or may be the target for future interventional strategies. Such insights may also enable improved power analyses and statistical designs that may be able to adjust for the confounds of such mixed pathologic disease states that are common in ADRD clinical trials.
Latent space projection of brain FDG‐PET creates a powerful classifier for neurodegenerative diseases
Authors: Barnard Leland R , Botha Hugo , Corriveau‐Lecavalier Nick , Dicks Ellen , Lee Jeyeon , Min Paul H , Senjem Matthew L. , Gunter Jeffrey L. , Schwarz Christopher G. , Boeve Bradley F. , Knopman David S. , Lowe Val J. , Petersen Ronald C. , Jack Clifford R. , Graff‐Radford Jonathan , Jones David T. 
Published: December 2022

AbstractBackgroundFluorodeoxyglucose positron emission tomography (FDG‐PET) is an established modality for differential diagnosis of dementia. Deriving phenotypic signatures from FDG‐PET via machine learning is challenging due to the high dimensional nature of brain images relative to the generally small number of labeled examples available for training, the class imbalance among those labels, and the cooccurrence of multiple pathologies. In this study, we developed a multi‐class, multi‐label framework to address these challenges.MethodA database of clinically acquired PET/CT images from 3,000 unique patients was used to develop a latent space model using matrix decomposition. This model was then applied to images from a separate cohort of Mayo Clinic Alzheimer’s Disease Research Center participants (n=1,745) labeled as cognitively unimpaired (CU) (n=1,436) or with the following potentially co‐occurring phenotypes: Alzheimer’s disease (AD) (n=165), Lewy body dementia (DLB) (n=92), behavioral variant frontotemporal dementia (bvFTD) (n=43), semantic (svPPA) (n=10) and logopenic (lvPPA) (n=13) variant PPA, and posterior cortical atrophy (PCA) (n=17). A k‐nearest neighbors classifier that is robust to these imbalanced and overlapping labels was then trained on these examples. The resulting classifier was evaluated by area under receiver‐operator characteristic curve (ROC‐AUC) via leave one out cross validation, using clinical diagnosis as the gold standard.ResultROC curves and AUC scores for each phenotype are illustrated in Fig. 1a. Because the classifier is based on a k‐nearest neighbors connectivity matrix, it has a convenient graphical representation, where images are nodes and edges are drawn between an image and its set of nearest neighbors in latent space. A self‐organizing force directed graph constructed in this way is illustrated in Fig 1b, highlighting the strong separation of CU and degenerative images, as well as the segregation of each phenotype within the neurodegenerative region of the graph.ConclusionIn this study, we developed a machine learning framework for classification of neurodegenerative disease based on k‐nearest neighbor analysis in a low dimensional latent space projection of FDG‐PET images. By leveraging low‐dimensional representations and k‐nearest neighbors analysis, this framework is robust in multi‐class, multi‐label tasks with strong class imbalance and provides a highly interpretable graphical representation.
A novel oral formulation (CoM pat. pend.) of HP‐alpha‐cyclodextrin as a safe (not ototoxic) and convenient (oral) drug against Alzheimer’s disease
Authors: Wittkowski Knut M. 
Published: December 2022

AbstractBackgroundThere are few, if any, disease‐modifying treatments (DMTs) for AD. HP‐beta‐cyclodextrin (HPβCD) was effective in AD models and ph1/2 trials of overnight IV HPβCD qow showed reduction of CSF tau protein, but also confirmed its risk of cholesterol‐related ototoxicity. As the hearing loss seen in these short (12 wk) trials was only transient (Fig. 1), the FDA accepted INDs for IV HPβCD as a drug against NPC1 (ph3) and AD (ph2).MethodTo avoid ototoxicity and the need for overnight infusion, we conducted a human PK/PD study of a novel (non‐covalent) clathrate of HPαCD and a milk/coconut oil medium‐chain fatty acid (capric acid, C10). HPαCD alone, co‐administered with, and as a clathrate with C10 (2:1 molar) were administered orally before bedtime. HPαCD and phospholipids (PLs) were measured by FPLC in morning urine. We also conducted animal studies in breast cancer and fast progressing neurodegenerative diseases (ALS/HD), where high levels of endocytosis are also known to “derail” the endocytosis‐lysosome‐autophagy (ELA) axis.ResultIP animal studies had showed HPαCD as more effective than HPβCD in breast cancer (reducing endocytosis and inflammation) While aCDs are reducing obesity in WT animals (and humans), HPaCD increasing bodyweight as a DMT in models of ALS?HD. Clinically, some HPαCD and PLs appeared in morning urine after oral administration as a mixture, but twice as much with the clathrate (Fig. 3).ConclusionIntermittent fasting (IF) and the IF mimetic HPαCD (too small to fit cholesterol) are not only effective against ALS, but were previously shown to be at least as effective as HPβCD in lysosomal storage diseases (LSDs, Fig. 4) and more effective in cancer, where endocytosis is also involved, albeit with different manifestations (Ancidoni 2021) (Fig. 5). With the new results showing that (a) the HPαCD clathrate ASD‐005 is
intestinally absorbed
, safe, and has
systemic effects in other ELA axis diseases
and (b) HP‐CDs are
active across the blood‐brain barrier
(Fig. 1), oral HP‐cyclodextrin clathrates are now emerging as more convenient, safer, and often more effective DMTs for AD or, when formulated with the GRAS aCD, as nutraceuticals to improve neurologic and cardiometabolic health in aging (ASD‐NP6).