Alzheimer\'s disease (AD) is the frequent form of dementia in the world. Despite over 100 years of research into the causes of AD, including amyloid and tau protein, the research has stalled and has not led to any conclusions. Moreover, numerous projects aimed at finding a cure for AD have also failed to achieve a breakthrough. Thus, the failure of anti-amyloid and anti-tau protein therapy to treat AD significantly influenced the way we began to think about the etiology of the disease. This situation prompted a group of researchers to focus on ischemic brain episodes, which, like AD, mostly present alterations in the hippocampus. In this context, it has been proposed that cerebral ischemic incidents may play a major role in promoting amyloid and tau protein in neurodegeneration in AD. In this review, we summarized the experimental and clinical research conducted over several years on the role of ischemic brain episodes in the development of AD. Studies have shown changes typical of AD in the course of brain neurodegeneration post-ischemia, i.e., progressive brain and hippocampal atrophy, increased amyloid production, and modification of tau protein. In the post-ischemic brain, the diffuse and senile amyloid plaques and the development of neurofibrillary tangles characteristic of AD were revealed. The above data evidently showed that after brain ischemia, there are modifications in protein folding, leading to massive neuronal death and damage to the neuronal network, which triggers dementia with the AD phenotype.

Established drug therapies for Alzheimer disease (cholinesterase inhibitors and memantine) do not modify the disease course and provide only modest clinical benefit. Biomarker measures of amyloid, tau and neurodegeneration have been integral to Alzheimer disease clinical trials for biologic drugs, for patient selection and efficacy monitoring. At the time of writing, two monoclonal antibodies targeting the amyloid-beta protein (aducanumab and lecanemab) have been approved in the USA, and two agents (lecanemab and donanemab) are under evaluation by the Therapeutic Goods Administration in Australia. Clinical trials have demonstrated that monoclonal antibodies are effective at removing amyloid from the brain in people with early Alzheimer disease. Cognitive benefits are statistically significant, but do not achieve the minimal clinically important difference. Amyloid-related imaging abnormalities of vasogenic oedema and microhaemorrhages occur more frequently on treatment; although these are usually asymptomatic or transient, in some people they are serious or fatal. Targeting amyloid as a unimodal strategy is unlikely to be sufficient and future therapies may need to be multimodal, targeting multiple pathogenic pathways. The burden of dementia is greatest in the older population where mixed dementia pathology dominates; the relationship between biomarkers, clinical phenotype and pathology attenuates; and frailty and comorbidity impact cognition. This creates challenges in identifying effective therapies for the group where dementia is most prevalent.

BACKGROUND: Leveraging Alzheimer\'s disease (AD) imaging biomarkers and longitudinal cognitive data may allow us to establish evidence of cognitive resilience (CR) to AD pathology in-vivo. Here, we applied latent class mixture modeling, adjusting for sex, baseline age, and neuroimaging biomarkers of amyloid, tau and neurodegeneration, to a sample of cognitively unimpaired older adults to identify longitudinal trajectories of CR.
METHODS: We identified 200 Harvard Aging Brain Study (HABS) participants (mean age = 71.89 years, SD = 9.41 years, 59% women) who were cognitively unimpaired at baseline with 2 or more timepoints of cognitive assessment following a single amyloid-PET, tau-PET and structural MRI. We examined latent class mixture models with longitudinal cognition as the dependent variable and time from baseline, baseline age, sex, neocortical Aβ, entorhinal tau, and adjusted hippocampal volume as independent variables. We then examined group differences in CR-related factors across the identified subgroups from a favored model. Finally, we applied our favored model to a dataset from the Alzheimer\'s Disease Neuroimaging Initiative (ADNI; n = 160, mean age = 73.9 years, SD = 7.6 years, 60% women).
RESULTS: The favored model identified 3 latent subgroups, which we labelled as Normal (71% of HABS sample), Resilient (22.5%) and Declining (6.5%) subgroups. The Resilient subgroup exhibited higher baseline cognitive performance and a stable cognitive slope. They were differentiated from other groups by higher levels of verbal intelligence and past cognitive activity. In ADNI, this model identified a larger Normal subgroup (88.1%), a smaller Resilient subgroup (6.3%) and a Declining group (5.6%) with a lower cognitive baseline.
CONCLUSIONS: These findings demonstrate the value of data-driven approaches to identify longitudinal CR groups in preclinical AD. With such an approach, we identified a CR subgroup who reflected expected characteristics based on previous literature, higher levels of verbal intelligence and past cognitive activity.

Repairing multiphasic defects is cumbersome. This study presents new soft and hard scaffold designs aimed at facilitating the regeneration of multiphasic defects by enhancing angiogenesis and improving cell attachment. Here, the nonimmunogenic, nontoxic, and cost-effective human serum albumin (HSA) fibril (HSA-F) was used to fabricate thermostable (up to 90 °C) and hard printable polymers. Additionally, using a 10.0 mg/mL HSA-F, an innovative hydrogel was synthesized in a mixture with 2.0% chitosan-conjugated arginine, which can gel in a cell-friendly and pH physiological environment (pH 7.4). The presence of HSA-F in both hard and soft scaffolds led to an increase in significant attachment of the scaffolds to the human periodontal ligament fibroblast (PDLF), human umbilical vein endothelial cell (HUVEC), and human osteoblast. Further studies showed that migration (up to 157%), proliferation (up to 400%), and metabolism (up to 210%) of these cells have also improved in the direction of tissue repair. By examining different in vitro and ex ovo experiments, we observed that the final multiphasic scaffold can increase blood vessel density in the process of per-vascularization as well as angiogenesis. By providing a coculture environment including PDLF and HUVEC, important cross-talk between these two cells prevails in the presence of roxadustat drug, a proangiogenic in this study. In vitro and ex ovo results demonstrated significant enhancements in the angiogenic response and cell attachment, indicating the effectiveness of the proposed design. This approach holds promise for the regeneration of complex tissue defects by providing a conducive environment for vascularization and cellular integration, thus promoting tissue healing.

UNASSIGNED: Studying the spatiotemporal patterns of amyloid accumulation in the brain over time is crucial in understanding Alzheimer\'s disease (AD). Positron Emission Tomography (PET) imaging plays a pivotal role because it allows for the visualization and quantification of abnormal amyloid beta (Aβ) load in the living brain, providing a powerful tool for tracking disease progression and evaluating the efficacy of anti-amyloid therapies. Generative artificial intelligence (AI) can learn complex data distributions and generate realistic synthetic images. In this study, we demonstrate for the first time the potential of Generative Adversarial Networks (GANs) to build a low-dimensional representation space that effectively describes brain amyloid load and its dynamics.
UNASSIGNED: Using a cohort of 1,259 subjects with AV45 PET images from the Alzheimer\'s Disease Neuroimaging Initiative (ADNI), we develop a 3D GAN model to project images into a latent representation space and generate back synthetic images. Then, we build a progression model on the representation space based on non-parametric ordinary differential equations to study brain amyloid evolution.
UNASSIGNED: We found that global SUVR can be accurately predicted with a linear regression model only from the latent representation space (RMSE = 0.08 ± 0.01). We generated synthetic PET trajectories and illustrated predicted Aβ change in four years compared with actual progression.
UNASSIGNED: Generative AI can generate rich representations for statistical prediction and progression modeling and simulate evolution in synthetic patients, providing an invaluable tool for understanding AD, assisting in diagnosis, and designing clinical trials. The aim of this study was to illustrate the huge potential that generative AI has in brain amyloid imaging and to encourage its advancement by providing use cases and ideas for future research tracks.

The conversion of a soluble protein into polymeric amyloid structures is a process that is poorly understood. Here, we describe a fully redox-regulated amyloid system in which cysteine oxidation of the tumor suppressor protein p16INK4a leads to rapid amyloid formation. We identify a partially-structured disulfide-bonded dimeric intermediate species that subsequently assembles into fibrils. The stable amyloid structures disassemble when the disulfide bond is reduced. p16INK4a is frequently mutated in cancers and is considered highly vulnerable to single-point mutations. We find that multiple cancer-related mutations show increased amyloid formation propensity whereas mutations stabilizing the fold prevent transition into amyloid. The complex transition into amyloids and their structural stability is therefore strictly governed by redox reactions and a single regulatory disulfide bond.

Alzheimer\'s disease (AD), first diagnosed over a century ago, remains one of the major healthcare crises around the globe. Currently, there is no cure or effective treatment. The majority of drug development efforts to date have targeted reduction of amyloid-β peptide (Aβ). Drug development through inhibition of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1), resulted in promising early clinical studies. However, nearly all small molecule BACE1 inhibitor drugs failed to live up to expectations in later phase clinical trials, due to toxicity and efficacy issues. This commentary aims to provide a brief review of over two decades of BACE1 inhibitor drug development challenges and efforts for treatment of AD and prospects of future BACE1-based drugs.

Aggregation of aberrant fragment of plasma gelsolin, AGelD187N, is a crucial event underlying the pathophysiology of Finnish gelsolin amyloidosis, an inherited form of systemic amyloidosis. The amyloidogenic gelsolin fragment AGelD187N does not play any physiological role in the body, unlike most aggregating proteins related to other protein misfolding diseases. However, no therapeutic agents that specifically and effectively target and neutralize AGelD187N exist. We employed phage display technology to identify novel single-chain variable fragments (scFvs) that bind to different epitopes in the monomeric AGelD187N that were further maturated by variable domain shuffling and converted to antigen-binding fragment (Fab) antibodies. The generated antibody fragments had nanomolar binding affinity for full-length AGelD187N, as evaluated by biolayer interferometry. Importantly, all four Fabs selected for functional studies efficiently inhibited the amyloid formation of full-length AGelD187N as examined by thioflavin fluorescence assay and transmission electron microscopy. Two Fabs, neither of which bound to the previously proposed fibril-forming region of AGelD187N, completely blocked the amyloid formation of AGelD187N. Moreover, no small soluble aggregates, which are considered pathogenic species in protein misfolding diseases, were formed after successful inhibition of amyloid formation by the most promising aggregation inhibitor, as investigated by size exclusion chromatography combined with multi-angle light scattering. We conclude that all regions of the full-length AGelD187N are important in modulating its assembly into fibrils and that the discovered epitope-specific anti-AGelD187N antibody fragments provide a promising starting point for a disease-modifying therapy for gelsolin amyloidosis, which is currently lacking.

Over the past decades, accumulating evidence suggests that the gut microbiome exerts a key role in Alzheimer\'s disease (AD). The Alzheimer\'s Association Workgroup is updating the diagnostic criteria for AD, which changed the profiles and categorization of biomarkers from \"AT(N)\" to \"ATNIVS.\" Previously, most of studies focus on the correlation between the gut microbiome and amyloid beta deposition (\"A\"), the initial AD pathological feature triggering the \"downstream\" tauopathy and neurodegeneration. However, limited research investigated the interactions between the gut microbiome and other AD pathogenesis (\"TNIVS\"). In this review, we summarize current findings of the gut microbial characteristics in the whole spectrum of AD. Then, we describe the association of the gut microbiome with updated biomarker categories of AD pathogenesis. In addition, we outline the gut microbiome-related therapeutic strategies for AD. Finally, we discuss current key issues of the gut microbiome research in the AD field and future research directions. HIGHLIGHTS: The new revised criteria for Alzheimer\'s disease (AD) proposed by the Alzheimer\'s Association Workgroup have updated the profiles and categorization of biomarkers from \"AT(N)\" to \"ATNIVS.\" The associations of the gut microbiome with updated biomarker categories of AD pathogenesis are described. Current findings of the gut microbial characteristics in the whole spectrum of AD are summarized. Therapeutic strategies for AD based on the gut microbiome are proposed.

BACKGROUND: Trisomy 21, or Down syndrome (DS), predisposes individuals to early-onset Alzheimer\'s disease (AD). While monoclonal antibodies (mAbs) targeting amyloid are approved for older AD patients, their efficacy in DS remains unexplored. This study examines amyloid positron emission tomography (PET) positivity (A+), memory function, and clinical status across ages in DS to guide mAb trial designs.
METHODS: Cross-sectional data from the Alzheimer Biomarker Consortium-Down Syndrome (ABC-DS) was analyzed. PET amyloid beta in Centiloids classified amyloid status using various cutoffs. Episodic memory was assessed using the modified Cued Recall Test, and clinical status was determined through consensus processes.
RESULTS: Four hundred nine DS adults (mean age = 44.83 years) were evaluated. A+ rates increased with age, with mean amyloid load rising significantly. Memory decline and cognitive impairment are also correlated with age.
CONCLUSIONS: These findings emphasize the necessity of tailoring mAb trials for DS, considering age-related AD characteristics.
CONCLUSIONS: There is rapid increase in prevalence of amyloid beta (Aβ) positron emission tomography (PET) positivity in Down syndrome (DS) after the age of 40 years. Aβ PET positivity thresholds have significant impact on prevalence rates in DS. There is a significant lag between Aβ PET positivity and clinical symptom onset in DS.