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Background: Previous studies have demonstrated associations between gut microbiota, microbial metabolites, and cognitive decline. However, relationships between these factors and neurofilament light chain (NfL; a disease-nonspecific biomarker of neural damage) remain controversial. Objective: To evaluate the associations between plasma NfL, gut microbiota, and cognitive function. Methods: We performed a cross-sectional sub-analysis of data from our prospective cohort study that was designed to investigate the relationship between gut microbiota and cognitive function. Patients who visited our memory clinic were enrolled and demographics, dementia-related risk factors, cognitive function, brain imaging, gut microbiomes, and microbial metabolites were assessed. We evaluated the relationships between the gut microbiome, microbial metabolites, and plasma NfL. Moreover, the relationships between plasma NfL and cognitive function were assessed using multivariable logistic regression analyses. Results: We analyzed 128 participants (women: 59%, mean age: 74 years). Participants with high (above the median) plasma NfL concentrations tended to be older, women, and hypertensive and have a history of stroke, chronic kidney disease, and dementia. Plasma NfL was also associated with cerebral small vessel disease. However, plasma NfL levels were not significantly correlated with gut microbial metabolites. Multivariable analyses revealed that a higher plasma NfL concentration was independently associated with the presence of dementia (odds ratio: 9.94, 95% confidence interval: 2.75–48.2, p

Background: While both apolipoprotein E (APOE) genotype and diabetes affect longevity as well as Alzheimer’s disease, their relationship remains to be elucidated. Objective: The current study investigated the potential interaction between diabetes and APOE for lifespan and their relationship with cognitive status. Methods: We reviewed the National Alzheimer’s Coordinating Center (NACC) dataset, which documents longitudinally clinical records of 24,967 individuals with APOE genotype and diabetic status. Results: Diabetes was associated with shorter lifespan in APOE3 carriers (n = 12,415, HR = 1.29, 95%CI = 1.17–1.42, p

Carriers of the apolipoprotein E ε4 allele (APOEɛ4) have an increased risk of developing dementia (e.g., Alzheimer's disease). However, it is less clear whether the APOEɛ4 might also be involved in cognitive aging among the non-clinical population of older adults. While some studies have suggested that the APOEɛ4 is related to accelerated cognitive decline in the normal aging process, others have failed to provide compelling evidence of such an impact. Notably, these discrepancies may depend on methodological shortcomings, including short time spans, few assessments, and small sample sizes. The present study overcomes the above limitations and aims to clarify the impact of the APOEɛ4 genotype on long-term longitudinal changes in cognitive functions in middle-aged and older adults in Japan.The data were retrieved from the National Institute for Longevity Sciences-Longitudinal Study of Aging (NILS-LSA) survey (N = 1832; 40 to 79 years of age at baseline). The participants were tested over nine waves covering a period of approximately 20 years. Latent Growth Curve (LGC) modeling was employed to test the impact of the interaction between APOEɛ4 status and age on several cognitive functions. Four tests of the WAIS-R were administered: Information, Similarities, Picture completion, and Digit Symbol Substitution Test (DSST). The results showed that the APOEɛ4 carriers experienced a more pronounced decline in the DSST (p = 0.001) and Similarities (p = 0.022) tests. A similar tendency was found in the Information test (p = 0.034). By contrast, no effect was found in the Picture completion test (p = 0.563).APOEɛ4 carriers seem to exhibit a steeper cognitive decline, which becomes apparent in old age. This effect is more robust in fluid cognitive skills (DSST) than crystallized cognitive skills (Information and Similarities). Overall, the APOEɛ4 genotype may be a significant risk factor in normal (i.e., non-clinical) cognitive aging.

Background: Previous studies have demonstrated associations between gut microbiota, microbial metabolites, and cognitive decline. However, relationships between these factors and neurofilament light chain (NfL; a disease-nonspecific biomarker of neural damage) remain controversial. Objective: To evaluate the associations between plasma NfL, gut microbiota, and cognitive function. Methods: We performed a cross-sectional sub-analysis of data from our prospective cohort study that was designed to investigate the relationship between gut microbiota and cognitive function. Patients who visited our memory clinic were enrolled and demographics, dementia-related risk factors, cognitive function, brain imaging, gut microbiomes, and microbial metabolites were assessed. We evaluated the relationships between the gut microbiome, microbial metabolites, and plasma NfL. Moreover, the relationships between plasma NfL and cognitive function were assessed using multivariable logistic regression analyses. Results: We analyzed 128 participants (women: 59%, mean age: 74 years). Participants with high (above the median) plasma NfL concentrations tended to be older, women, and hypertensive and have a history of stroke, chronic kidney disease, and dementia. Plasma NfL was also associated with cerebral small vessel disease. However, plasma NfL levels were not significantlycorrelatedwithgutmicrobialmetabolites.MultivariableanalysesrevealedthatahigherplasmaNfLconcentration was independently associated with the presence of dementia (odds ratio: 9.94, 95% confidence interval: 2.75–48.2, p < 0.001). Conclusion: High plasma NfL concentration was independently associated with the presence of dementia as previously reported. However, plasma NfL levels were not significantly correlated with gut microbial metabolites in this preliminary study.

Clinical studies have indicated that obesity and diabetes are associated with Alzheimer's disease (AD) and neurodegeneration. However, the mechanism by which obesity/diabetes and AD interact with each other and contribute to dementia remains elusive. To obtain insights into their interaction at molecular levels, we performed gene expression analysis of APP;ob/ob mice, which were generated by crossing transgenic AD model mice (APP23 mice) with ob/ob mice, which are obese and mildly diabetic. The Aβ level in these mice was reduced compared with that in pure APP mice. However, we identified a cluster of genes (cluster 10) upregulated in APP;ob/ob mice but not in either APP or ob/ob mice. Interestingly, genes upregulated in the human AD brain were enriched in cluster 10. Moreover, genes in cluster 10 formed a network and shared upregulated genes with a cell model of neurodegeneration and other models of neurological disorders such as ischemia and epilepsy. In silico analyses showed that serum response factor (SRF), recently identified in a single‐cell analysis of human brains as a transcription factor that can control the conversion from healthy cells to AD cells, might be a common transcriptional regulator for a subset of cluster 10 genes. These data suggest that upregulation of genes uniquely associated with APP;ob/ob mice is an evidence of the interaction between obesity/diabetes and AD.

Biochar-immobilized potassium nickel hexacyanoferrate (KNiFC) as a sorbent for removal of radioactive cesium (Cs) from aqueous solutions was prepared using a novel method. Japanese cedar sawdust loaded with NiSO4 using a ball mill was carbonized at various temperatures. The resultant Ni-loaded biochar was immersed in a K4[Fe(CN)6]·3H2O solution, and biochar-immobilized KNiFC was obtained. For comparison, Ni-loaded biochar was also prepared using the impregnation method. The loading of Ni using the ball mill resulted in a higher Ni amount in the biochar compared with the impregnation method. The carbonization at 400 °C was suitable for Cs adsorption on biochar and synthesis of KNiFC. Consequently, KNiFC immobilization on biochar improved the Cs sorption performance in aqueous solutions with Na+, K+, Ca2+, Mg2+, and Cs+. The sorption performance was selective in aqueous solutions with radioactive Cs and other cations of high concentration. Low-cost Cs adsorbent was prepared using a novel method from bioresource and KNiFC. The application of ball mill was effective for loading Ni on biochar. Immobilization of KNiFC on biochar improved Cs sorption performance. Removal of 134Cs and 137Cs using biochar-immobilized KNiFC was selective.

Convergent evidence has demonstrated that semantics are represented by the interaction between a multimodal semantic hub at the anterior temporal lobe (ATL) and other modality-specific association cortical areas. Electrocorticogram (ECoG) recording with high spatiotemporal resolutions is efficient in evaluating such cortical interactions; however, this has not been a focus of preceding studies. The present study evaluated cortical interactions during picture naming using a novel ECoG cross-spectrum analysis, which was formulated from a computational simulation of neuronal networks and combined with a vector space model of semantics. The results clarified three types of frequency-dependent cortical networks: 1) an earlier-period (0.2–0.8 s from stimulus onset) high-gamma-band (90–150 Hz) network with a hub at the posterior fusiform gyrus, 2) a later-period (0.4–1.0 s) beta-band (15–40 Hz) network with multiple hubs at the ventral ATL and posterior middle temporal gyrus, and 3) a pre-articulation theta-band (4–7 Hz) network distributed over widely located cortical regions. These results suggest that frequency-dependent cortical interactions can characterize the underlying processes of semantic cognition, and the beta-band network with a hub at the ventral ATL is especially associated with the formation of semantic representation.

Background: One main pathological hallmark of Alzheimer’s disease (AD) is tau accumulation as neurofibrillary tangles (NFTs) in the brain. Although sandwich enzyme-linked immunosorbent assays (ELISAs) are useful for quantifying tau levels, including those in CSF, plasma and brain, it has not yet been determined which antibody combination is the most appropriate for assessing the neuropathological accumulation of tau in the brain. Methods: We developed several sandwich tau ELISAs by introducing antibodies against several tau epitopes, including from its N-terminal and C-terminal regions, and evaluated tau levels depending on disease stage, brain areas, and other AD-related changes. Results: We observed that tau levels in insoluble brain fraction determined by each ELISAs differ depending on the epitopes of the antibodies: there is a trend that non-AD control samples yield relatively high signals when an antibody against the N-terminal region of tau is used. On the other hand, ELISAs combining two antibodies against the later-middle to C-terminal regions of tau produced substantially increased signals from AD samples, compared to those from non-AD controls. Such ELISAs better distinguish AD and non-AD controls, and the results are more closely associated with Braak NFT stage, Aβ accumulation, and neuroinflammatory markers. In addition, these ELISAs can reflect the pattern of tau spread across brain regions. Conclusions: Tau ELISAs that combine two antibodies against the later-middle to C-terminal regions of tau can better reflect neuropathological tau accumulation, which would enable to evaluate tau accumulation in the brain at a biochemical level.

Clinical studies have indicated that obesity and diabetes are associated with Alzheimer's disease (AD) and neurodegeneration. However, the mechanism by which obesity/diabetes and AD interact with each other and contribute to dementia remains elusive. To obtain insights into their interaction at molecular levels, we performed gene expression analysis of APP;ob/ob mice, which were generated by crossing transgenic AD model mice (APP23 mice) with ob/ob mice, which are obese and mildly diabetic. The Aβ level in these mice was reduced compared with that in pure APP mice. However, we identified a cluster of genes (cluster 10) upregulated in APP;ob/ob mice but not in either APP or ob/ob mice. Interestingly, genes upregulated in the human AD brain were enriched in cluster 10. Moreover, genes in cluster 10 formed a network and shared upregulated genes with a cell model of neurodegeneration and other models of neurological disorders such as ischemia and epilepsy. In silico analyses showed that serum response factor (SRF), recently identified in a single‐cell analysis of human brains as a transcription factor that can control the conversion from healthy cells to AD cells, might be a common transcriptional regulator for a subset of cluster 10 genes. These data suggest that upregulation of genes uniquely associated with APP;ob/ob mice is an evidence of the interaction between obesity/diabetes and AD.