Targeting Impaired Antimicrobial Immunity in the Brain for the Treatment of Alzheimer’s Disease
Bibliographic record
Abstract
Tamas Fulop,1 Shreyansh Tripathi,2,3 Serafim Rodrigues,3,4 Mathieu Desroches,5,6 Ton Bunt,7 Arnold Eiser,8 Francois Bernier,9 Pascale B Beauregard,10 Annelise E Barron,11 Abdelouahed Khalil,1 Adam Plotka,12 Katsuiku Hirokawa,13 Anis Larbi,14 Christian Bocti,15 Benoit Laurent,16 Eric H Frost,17 Jacek M Witkowski12 1Research Center on Aging, Geriatric Division, Department of Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada; 2Cluster Innovation Centre, North Campus, University of Delhi, Delhi, 110007, India; 3Ikerbasque, The Basque Foundation for Science, Bilbao, Spain; 4Mathematical Computational and Experimental Neuroscience (MCEN), BCAM - The Basque Center for Applied Mathematics, Bilbao, Spain; 5MathNeuro Team, Inria Sophia Antipolis Méditerranée, Sophia Antipolis, France; 6Department of Mathematics, Université Côte d’Azur, Nice, France; 7Izumi Biosciences, Inc., Lexington, MA, USA; 8Leonard Davis Institute, University of Pennsylvania, Drexel University College of Medicine, Philadelphia, PA, USA; 9Morinaga Milk Industry Co., Ltd, Next Generation Science Institute, Kanagawa, Japan; 10Department of Biology, Faculty of Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada; 11Department of Bioengineering, Stanford School of Medicine, Stanford, CA, USA; 12Department of Pathophysiology, Medical University of Gdansk, Gdansk, Poland; 13Institute of Health and Life Science, Tokyo Med. Dent. University, Tokyo and Nito-Memory Nakanosogo Hospital, Department of Pathology, Tokyo, Japan; 14Singapore Immunology Network (SIgN), Agency for Science Technology and Research (A*STAR), Immunos Building, Biopolis, Singapore, Singapore; 15Research Center on Aging, Department of Medicine, Division of Neurology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada; 16Research Center on Aging, Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada; 17Department of Microbiology and Infectious Diseases, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, CanadaCorrespondence: Tamas FulopResearch Center on Aging, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 3001, 12th Avenue North, Sherbrooke, Quebec, J1H 5N4, CanadaTel +1 819 780 2220Fax +1 819 829 7141Email tamas.fulop@usherbrooke.caSerafim RodriguesIkerbasque Prof. Dr., Ikerbasque, The Basque Foundation for Science Bilbao, Spain and BCAM - The Basque Center for Applied Mathematics, Mathematical, Computational and Experimental (MCEN) Research Group, Alameda de Mazarredo 14, Bilbao, Bizkaia, Basque-Country, 48009, SpainTel +34 946 567 842Email srodrigues@bcamath.orgAbstract: Alzheimer’s disease (AD) is the most common form of dementia and aging is the most common risk factor for developing the disease. The etiology of AD is not known but AD may be considered as a clinical syndrome with multiple causal pathways contributing to it. The amyloid cascade hypothesis, claiming that excess production or reduced clearance of amyloid-beta (Aβ) and its aggregation into amyloid plaques, was accepted for a long time as the main cause of AD. However, many studies showed that Aβ is a frequent consequence of many challenges/pathologic processes occurring in the brain for decades. A key factor, sustained by experimental data, is that low-grade infection leading to production and deposition of Aβ, which has antimicrobial activity, precedes the development of clinically apparent AD. This infection is chronic, low grade, largely clinically silent for decades because of a nearly efficient antimicrobial immune response in the brain. A chronic inflammatory state is induced that results in neurodegeneration. Interventions that appear to prevent, retard or mitigate the development of AD also appear to modify the disease. In this review, we conceptualize further that the changes in the brain antimicrobial immune response during aging and especially in AD sufferers serve as a foundation that could lead to improved treatment strategies for preventing or decreasing the progression of AD in a disease-modifying treatment.Keywords: Alzheimer’s disease, mild cognitive impairment, neuroinflammation, antimicrobial immunity, brain, treatment
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".