Objectives: This study aimed to investigate the relationship between blood microbiota,specifically bacterial DNA, and cognitive decline in individuals with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The objective was to identify potential microbial signatures that could serve as biomarkers for cognitive deterioration. Methods: Forty-seven participants were recruited, including 13 with aMCI, 20 with SCD, and 14 normal cognition (NC). Blood samples were collected, and microbial DNA was analyzed using 16S rRNA sequencing on the Illumina MiSeq platform. Bioinformatics analyses—including α- and β-diversity measures and differential abundance testing (using edgeR)—were employed to assess microbial diversity and differences in bacterial composition among groups. Logistic regression models were used to evaluate the predictive impact of the microbiota on cognitive decline. Results: Microbial diversity differed significantly between groups, with NC exhibiting the highest α-diversity. Both the aMCI and SCD groups showed reduced diversity. Taxa such as Bacteroidia, Alphaproteobacteria, and Clostridia were significantly decreased in the aMCI group compared to NC (p < 0.05). In contrast, Gammaproteobacteria increased significantly in the aMCI group compared to both NC and SCD, indicating progressive microbial changes from SCD to aMCI. No significant differences were found between the NC and SCD groups. Conclusion Distinct bacterial taxa—particularly the increase in Gammaproteobacteria along with decreases in Bacteroidia, Alphaproteobacteria, and Clostridia—are associated with the progression of cognitive decline. These findings suggest that blood microbiota could serve as potential biomarkers for the early detection of aMCI. However, the small sample size and the lack of control for confounding factors such as diet and medication limit the findings. Larger studies are needed to validate these results and further explore the role of microbiota in neurodegeneration.

Objectives: This study aimed to investigate the relationship between blood microbiota,specifically bacterial DNA, and cognitive decline in individuals with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The objective was to identify potential microbial signatures that could serve as biomarkers for cognitive deterioration. Methods: Forty-seven participants were recruited, including 13 with aMCI, 20 with SCD, and 14 normal cognition (NC). Blood samples were collected, and microbial DNA was analyzed using 16S rRNA sequencing on the Illumina MiSeq platform. Bioinformatics analyses—including α- and β-diversity measures and differential abundance testing (using edgeR)—were employed to assess microbial diversity and differences in bacterial composition among groups. Logistic regression models were used to evaluate the predictive impact of the microbiota on cognitive decline. Results: Microbial diversity differed significantly between groups, with NC exhibiting the highest α-diversity. Both the aMCI and SCD groups showed reduced diversity. Taxa such as Bacteroidia, Alphaproteobacteria, and Clostridia were significantly decreased in the aMCI group compared to NC (p < 0.05). In contrast, Gammaproteobacteria increased significantly in the aMCI group compared to both NC and SCD, indicating progressive microbial changes from SCD to aMCI. No significant differences were found between the NC and SCD groups. Conclusion Distinct bacterial taxa—particularly the increase in Gammaproteobacteria along with decreases in Bacteroidia, Alphaproteobacteria, and Clostridia—are associated with the progression of cognitive decline. These findings suggest that blood microbiota could serve as potential biomarkers for the early detection of aMCI. However, the small sample size and the lack of control for confounding factors such as diet and medication limit the findings. Larger studies are needed to validate these results and further explore the role of microbiota in neurodegeneration.

Objectives: This study aimed to investigate the relationship between blood microbiota,specifically bacterial DNA, and cognitive decline in individuals with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The objective was to identify potential microbial signatures that could serve as biomarkers for cognitive deterioration. Methods: Forty-seven participants were recruited, including 13 with aMCI, 20 with SCD, and 14 normal cognition (NC). Blood samples were collected, and microbial DNA was analyzed using 16S rRNA sequencing on the Illumina MiSeq platform. Bioinformatics analyses—including α- and β-diversity measures and differential abundance testing (using edgeR)—were employed to assess microbial diversity and differences in bacterial composition among groups. Logistic regression models were used to evaluate the predictive impact of the microbiota on cognitive decline. Results: Microbial diversity differed significantly between groups, with NC exhibiting the highest α-diversity. Both the aMCI and SCD groups showed reduced diversity. Taxa such as Bacteroidia, Alphaproteobacteria, and Clostridia were significantly decreased in the aMCI group compared to NC (p < 0.05). In contrast, Gammaproteobacteria increased significantly in the aMCI group compared to both NC and SCD, indicating progressive microbial changes from SCD to aMCI. No significant differences were found between the NC and SCD groups. Conclusion Distinct bacterial taxa—particularly the increase in Gammaproteobacteria along with decreases in Bacteroidia, Alphaproteobacteria, and Clostridia—are associated with the progression of cognitive decline. These findings suggest that blood microbiota could serve as potential biomarkers for the early detection of aMCI. However, the small sample size and the lack of control for confounding factors such as diet and medication limit the findings. Larger studies are needed to validate these results and further explore the role of microbiota in neurodegeneration.

Objectives: This study aimed to investigate the relationship between blood microbiota,specifically bacterial DNA, and cognitive decline in individuals with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The objective was to identify potential microbial signatures that could serve as biomarkers for cognitive deterioration. Methods: Forty-seven participants were recruited, including 13 with aMCI, 20 with SCD, and 14 normal cognition (NC). Blood samples were collected, and microbial DNA was analyzed using 16S rRNA sequencing on the Illumina MiSeq platform. Bioinformatics analyses—including α- and β-diversity measures and differential abundance testing (using edgeR)—were employed to assess microbial diversity and differences in bacterial composition among groups. Logistic regression models were used to evaluate the predictive impact of the microbiota on cognitive decline. Results: Microbial diversity differed significantly between groups, with NC exhibiting the highest α-diversity. Both the aMCI and SCD groups showed reduced diversity. Taxa such as Bacteroidia, Alphaproteobacteria, and Clostridia were significantly decreased in the aMCI group compared to NC (p < 0.05). In contrast, Gammaproteobacteria increased significantly in the aMCI group compared to both NC and SCD, indicating progressive microbial changes from SCD to aMCI. No significant differences were found between the NC and SCD groups. Conclusion Distinct bacterial taxa—particularly the increase in Gammaproteobacteria along with decreases in Bacteroidia, Alphaproteobacteria, and Clostridia—are associated with the progression of cognitive decline. These findings suggest that blood microbiota could serve as potential biomarkers for the early detection of aMCI. However, the small sample size and the lack of control for confounding factors such as diet and medication limit the findings. Larger studies are needed to validate these results and further explore the role of microbiota in neurodegeneration.

Objectives: This study aimed to investigate the relationship between blood microbiota,specifically bacterial DNA, and cognitive decline in individuals with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The objective was to identify potential microbial signatures that could serve as biomarkers for cognitive deterioration. Methods: Forty-seven participants were recruited, including 13 with aMCI, 20 with SCD, and 14 normal cognition (NC). Blood samples were collected, and microbial DNA was analyzed using 16S rRNA sequencing on the Illumina MiSeq platform. Bioinformatics analyses—including α- and β-diversity measures and differential abundance testing (using edgeR)—were employed to assess microbial diversity and differences in bacterial composition among groups. Logistic regression models were used to evaluate the predictive impact of the microbiota on cognitive decline. Results: Microbial diversity differed significantly between groups, with NC exhibiting the highest α-diversity. Both the aMCI and SCD groups showed reduced diversity. Taxa such as Bacteroidia, Alphaproteobacteria, and Clostridia were significantly decreased in the aMCI group compared to NC (p < 0.05). In contrast, Gammaproteobacteria increased significantly in the aMCI group compared to both NC and SCD, indicating progressive microbial changes from SCD to aMCI. No significant differences were found between the NC and SCD groups. Conclusion Distinct bacterial taxa—particularly the increase in Gammaproteobacteria along with decreases in Bacteroidia, Alphaproteobacteria, and Clostridia—are associated with the progression of cognitive decline. These findings suggest that blood microbiota could serve as potential biomarkers for the early detection of aMCI. However, the small sample size and the lack of control for confounding factors such as diet and medication limit the findings. Larger studies are needed to validate these results and further explore the role of microbiota in neurodegeneration.

We investigated the stress-induced changes in the lipid and hormonal concentrations in plasma, including cytochrome P450 (CYP)-derived oxidative stress in the liver, and the anti-stresseffect of Korean Red Ginseng (KRG) water extract in mice. Stress induction using restraint increased the levels of corticosterone (CORT), glucose, total cholesterol (TC), and low-den-sity lipoprotein-cholesterol (LDL-C) while decreasing in the levels of insulin and high-density lipoprotein-cholesterol (HDL-C), compared with those of unstressed mice. Restraint-stress also increased the generation of reactive oxygen species (ROS) in plasma by 5.4-fold. More-over, the stress resulted in a 2.8-fold higher production of C-reactive protein (CRP) than the control group. In addition, the catalytic activities of CYP1A2 and CYP3A4 in the liver micro-somes were stimulated by 5.5- and 3.8-fold, respectively, and concomitant ROS formation was elevated by 4.3-fold in the liver extract, compared to the normal group. In contrast, the KRG treatment (5, 20, or 50 mg/kg/day) to stress-exposed 3 groups alleviated the increased CORT, TC, LDL-C, ROS, and CRP levels and restored the decreased insulin concentrations.The enhanced each ROS in the plasma and liver, and the CYP enzyme activities were also attenuated in KRG-treated mice in a concentration-dependent manner. In conclusion, these results suggest that KRG ameliorates stress-induced detrimental effects on the plasma and liver of treated mice.

We investigated the stress-induced changes in the lipid and hormonal concentrations in plasma, including cytochrome P450 (CYP)-derived oxidative stress in the liver, and the anti-stresseffect of Korean Red Ginseng (KRG) water extract in mice. Stress induction using restraint increased the levels of corticosterone (CORT), glucose, total cholesterol (TC), and low-den-sity lipoprotein-cholesterol (LDL-C) while decreasing in the levels of insulin and high-density lipoprotein-cholesterol (HDL-C), compared with those of unstressed mice. Restraint-stress also increased the generation of reactive oxygen species (ROS) in plasma by 5.4-fold. More-over, the stress resulted in a 2.8-fold higher production of C-reactive protein (CRP) than the control group. In addition, the catalytic activities of CYP1A2 and CYP3A4 in the liver micro-somes were stimulated by 5.5- and 3.8-fold, respectively, and concomitant ROS formation was elevated by 4.3-fold in the liver extract, compared to the normal group. In contrast, the KRG treatment (5, 20, or 50 mg/kg/day) to stress-exposed 3 groups alleviated the increased CORT, TC, LDL-C, ROS, and CRP levels and restored the decreased insulin concentrations.The enhanced each ROS in the plasma and liver, and the CYP enzyme activities were also attenuated in KRG-treated mice in a concentration-dependent manner. In conclusion, these results suggest that KRG ameliorates stress-induced detrimental effects on the plasma and liver of treated mice.

We investigated the stress-induced changes in the lipid and hormonal concentrations in plasma, including cytochrome P450 (CYP)-derived oxidative stress in the liver, and the anti-stresseffect of Korean Red Ginseng (KRG) water extract in mice. Stress induction using restraint increased the levels of corticosterone (CORT), glucose, total cholesterol (TC), and low-den-sity lipoprotein-cholesterol (LDL-C) while decreasing in the levels of insulin and high-density lipoprotein-cholesterol (HDL-C), compared with those of unstressed mice. Restraint-stress also increased the generation of reactive oxygen species (ROS) in plasma by 5.4-fold. More-over, the stress resulted in a 2.8-fold higher production of C-reactive protein (CRP) than the control group. In addition, the catalytic activities of CYP1A2 and CYP3A4 in the liver micro-somes were stimulated by 5.5- and 3.8-fold, respectively, and concomitant ROS formation was elevated by 4.3-fold in the liver extract, compared to the normal group. In contrast, the KRG treatment (5, 20, or 50 mg/kg/day) to stress-exposed 3 groups alleviated the increased CORT, TC, LDL-C, ROS, and CRP levels and restored the decreased insulin concentrations.The enhanced each ROS in the plasma and liver, and the CYP enzyme activities were also attenuated in KRG-treated mice in a concentration-dependent manner. In conclusion, these results suggest that KRG ameliorates stress-induced detrimental effects on the plasma and liver of treated mice.

Hearing thresholds provide essential information and references about the human auditory system. This study aimed to identify changing trends in distributions of hearing threshold levels across ages by comparing the International Organization for Standardization (ISO) 7029 and newly available data after publishing ISO 7029. To compare ISO 7029 and newly available hearing threshold data after publishing ISO 7029, four country-specific datasets that presented average hearing threshold levels under conditions similar to ISO 7029 were utilized. For frequencies between 125 Hz and 8,000 Hz, the deviations of hearing threshold values by ages from the hearing threshold of the youngest age group for each data point were utilized. For frequencies from 9,000 Hz to 12,500 Hz, the median threshold information was utilized. Hearing threshold data reported after publishing ISO 7029 from the four countries were mostly similar to the ISO 7029 data but tended to deviate in some age groups and sexes. As national hearing threshold trends change, the following ISO 7029 revision suggests the need to integrate hearing threshold data from different countries.

Background: Chlorogenic acid (CGA) has been shown to reduce pro-inflammation by scavenging reactive oxy‑ gen species (ROS) and reactive nitrogen species. In this study, the anti-inflammatory effect of CGA was expanded to streptozotocin (STZ)-induced diabetic rats. The inter-relationships among oxidative stress, pro-inflammation, and cytochrome P450 (CYP) 1A enzymes were also investigated in peripheral blood mononuclear cells (PBMC) of STZdiabetic rats. Results: The levels of pro-inflammatory cytokines, interleukin-6 and tumor necrosis factor-alpha, increased by approximately 3.4- and 2.9-fold, respectively, and the albumin concentration decreased in the serum of STZ-induced diabetic rats compared to normal rats. The C-reactive protein (CRP) values also increased by about 3.8-fold higher, indicating that STZ induced an inflammation in the blood of STZ-diabetic rats. The expression levels and catalytic activities of CYP1A enzymes were elevated by approximately 2.2–2.5- and 4.3–6.7-fold, respectively, in the PBMC of STZ-treated rats. A decrease in the amount of PBMC-bound albumin was also observed. In contrast, the levels of cytokines and CRP in serum and the activities of CYP1A enzymes in PBMC were significantly reduced in CGA-treated diabetic rats in a CGA concentration-dependent manner. In addition, STZ-mediated elevation of ROS in serum and PBMC was decreased by the CGA administration. However, the CGA treatment did not change the enhanced blood glucose level and expression of CYP1A enzymes by STZ. STZ-mediated decrease in the levels of serum and PBMCbound albumin was not also restored by the CGA administration. Conclusions These results suggest that CGA could be used to treat type 1 diabetes-induced inflammation.